Triple
T22813897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SPS North Area beamlines |
E565051
|
entity |
| Predicate | deliversParticlesTo |
P25626
|
FINISHED |
| Object | fixed-target experiments |
—
|
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: fixed-target experiments | Statement: [SPS North Area beamlines, deliversParticlesTo, fixed-target experiments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: deliversParticlesTo Context triple: [SPS North Area beamlines, deliversParticlesTo, fixed-target experiments]
-
A.
usedParticle
Indicates that one entity employs or applies a particular particle (e.g., subatomic, linguistic, or material) in some process, context, or construction involving another entity.
-
B.
involvesParticleEjection
Indicates that the action or process includes the emission or release of particles from a source.
-
C.
associatedWithParticle
Indicates that an entity has a contextual or functional connection to a specific particle (such as a subatomic particle or grammatical particle).
-
D.
beamParticle
chosen
Indicates that one entity directs or projects another entity as a beam-like stream or focused flow.
-
E.
sendsBodyPartsTo
Indicates that one entity transmits or delivers body parts to another 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_69e2458426188190b58b8ab4844fe420 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17d62b0ec8190ac22909192e8a876 |
completed | April 29, 2026, 3:39 a.m. |
| PD | Predicate disambiguation | batch_69eed2cb30f481909566369f515f6eff |
completed | April 27, 2026, 3:06 a.m. |
Created at: April 17, 2026, 3:32 p.m.