Triple
T6088110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Timepix pixel detector |
E135689
|
entity |
| Predicate | developedBy |
P73
|
FINISHED |
| Object |
Medipix Collaboration
The Medipix Collaboration is an international research consortium that designs and develops advanced pixel detector technologies for high-resolution particle and radiation imaging.
|
E566113
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Medipix Collaboration | Statement: [Timepix pixel detector, developedBy, Medipix Collaboration]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Medipix Collaboration Context triple: [Timepix pixel detector, developedBy, Medipix Collaboration]
-
A.
timepix pixel detector
The Timepix pixel detector is a high-resolution, time-stamping semiconductor pixel sensor technology used in particle physics experiments to precisely track and measure ionizing radiation.
-
B.
Silicon Pixel Detector
The Silicon Pixel Detector is a high-precision tracking device in particle physics experiments that uses finely segmented silicon sensors to measure charged particle trajectories close to the interaction point.
-
C.
Silicon Drift Detector
A Silicon Drift Detector is a type of semiconductor radiation detector that uses lateral electric fields to drift charge carriers to a small collecting anode, enabling high energy resolution and fast, low-noise signal readout in applications such as particle tracking and X-ray spectroscopy.
-
D.
Silicon Strip Detector
A Silicon Strip Detector is a type of semiconductor particle detector that uses parallel strips of silicon to precisely measure the position and trajectory of charged particles in high-energy physics experiments.
-
E.
Micromegas detectors
Micromegas detectors are high-granularity gaseous particle detectors that provide precise tracking and fast timing for high-energy physics experiments.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Medipix Collaboration Triple: [Timepix pixel detector, developedBy, Medipix Collaboration]
Generated description
The Medipix Collaboration is an international research consortium that designs and develops advanced pixel detector technologies for high-resolution particle and radiation imaging.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Medipix Collaboration Target entity description: The Medipix Collaboration is an international research consortium that designs and develops advanced pixel detector technologies for high-resolution particle and radiation imaging.
-
A.
timepix pixel detector
The Timepix pixel detector is a high-resolution, time-stamping semiconductor pixel sensor technology used in particle physics experiments to precisely track and measure ionizing radiation.
-
B.
Silicon Pixel Detector
The Silicon Pixel Detector is a high-precision tracking device in particle physics experiments that uses finely segmented silicon sensors to measure charged particle trajectories close to the interaction point.
-
C.
Silicon Drift Detector
A Silicon Drift Detector is a type of semiconductor radiation detector that uses lateral electric fields to drift charge carriers to a small collecting anode, enabling high energy resolution and fast, low-noise signal readout in applications such as particle tracking and X-ray spectroscopy.
-
D.
Silicon Strip Detector
A Silicon Strip Detector is a type of semiconductor particle detector that uses parallel strips of silicon to precisely measure the position and trajectory of charged particles in high-energy physics experiments.
-
E.
Micromegas detectors
Micromegas detectors are high-granularity gaseous particle detectors that provide precise tracking and fast timing for high-energy physics experiments.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c0087bcc788190b20f093d3a6c60ec |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c057a6f7588190b265d6005fbaf6b3 |
completed | March 22, 2026, 8:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c11d65908c8190a9700c0981dabe9a |
completed | March 23, 2026, 11 a.m. |
| NEDg | Description generation | batch_69c11dfb27bc81908c7109debc73249d |
completed | March 23, 2026, 11:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c11e7a5e7881908d5cc70cc11a58cd |
completed | March 23, 2026, 11:05 a.m. |
Created at: March 22, 2026, 4:12 p.m.