Triple
T8396808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Virgo Collaboration |
E198072
|
entity |
| Predicate | armLengthOfDetector |
P75639
|
FINISHED |
| Object | 3 km |
—
|
LITERAL FINISHED |
How this triple was built (2 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: 3 km | Statement: [Virgo Collaboration, armLengthOfDetector, 3 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: armLengthOfDetector Context triple: [Virgo Collaboration, armLengthOfDetector, 3 km]
-
A.
numberOfDetectors
Indicates the quantity of detectors associated with or involved in a given entity or system.
-
B.
hasFarDetector
Indicates that an entity is equipped with or associated with a detector positioned at a relatively large distance from a reference point or source.
-
C.
numberOfMainDetectors
Indicates the quantity of primary detectors associated with or used in a given context or system.
-
D.
dimensionOfLength
chosen
Indicates that something represents or specifies a measurement along a single spatial extent (a length dimension).
-
E.
hasChamberLength
Indicates the length measurement of a chamber associated with an entity.
- F. None of above.
Provenance (3 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_69ca82f816bc8190ab321c07d72208c1 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb818893348190a6ea2ff6a2e3e491 |
completed | March 31, 2026, 8:10 a.m. |
| PD | Predicate disambiguation | batch_69cb70d24b248190a326aa6804f942b5 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 6:04 p.m.