Triple
T1095761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NA48 |
E24267
|
entity |
| Predicate | usesBeam |
P5356
|
FINISHED |
| Object | proton beam from SPS |
—
|
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: proton beam from SPS | Statement: [NA48, usesBeam, proton beam from SPS]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesBeam Context triple: [NA48, usesBeam, proton beam from SPS]
-
A.
hasTypicalBeam
Indicates that an entity is associated with a characteristic or standard type of beam it commonly uses or possesses.
-
B.
usesPrimaryBeam
chosen
Indicates that one entity employs another entity as its main or principal beam in an operation or structure.
-
C.
beam
Indicates that one entity emits, directs, or projects a concentrated line or stream (such as light, energy, or information) toward another entity.
-
D.
usesCanons
Indicates that one entity employs or makes use of canons (such as rules, principles, or artillery pieces) in relation to another entity or context.
-
E.
usesLaserType
Indicates that one entity employs or operates a specific type or category of laser in performing an action or function.
- 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_69a4940542308190ac2a0b1f730b7cfc |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b99e92308190b8a8c499e1630672 |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b7448c148190a3c9a4158ebd05b4 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.