Triple
T6058146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Compact Muon Solenoid |
E134964
|
entity |
| Predicate | collidesParticleType |
P68022
|
FINISHED |
| Object | protons |
—
|
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: protons | Statement: [Compact Muon Solenoid, collidesParticleType, protons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: collidesParticleType Context triple: [Compact Muon Solenoid, collidesParticleType, protons]
-
A.
collisionType
Indicates the specific kind or category of collision that occurs between two or more entities.
-
B.
colliderType
Indicates the type or category of physical collision behavior defined for an object in a simulation or physics system.
-
C.
collidesWith
Indicates that two entities come into contact with each other in space, typically implying an impact or physical intersection of their paths or volumes.
-
D.
hasParticleType
Indicates that an entity is associated with, composed of, or characterized by a specific type or category of particle.
-
E.
collisionDetectionMethod
Indicates the technique or algorithm used to determine whether two or more entities come into contact or intersect.
- F. None of above. chosen
Provenance (4 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_69c00877b6d4819096b0e163728b73a3 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0570d00e88190b2d8d596e40378d9 |
completed | March 22, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69c049edc6f0819092ca620d9073ad26 |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04dbefd1081909795fe1a812b991a |
completed | March 22, 2026, 8:14 p.m. |
Created at: March 22, 2026, 4:10 p.m.