Triple
T1160869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NA61/SHINE |
E24486
|
entity |
| Predicate | usesTargetType |
P23634
|
FINISHED |
| Object | fixed target |
—
|
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 | Statement: [NA61/SHINE, usesTargetType, fixed target]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesTargetType Context triple: [NA61/SHINE, usesTargetType, fixed target]
-
A.
supportsTargetType
chosen
Indicates that one entity is capable of operating with, handling, or being compatible with a specified target type.
-
B.
hasTarget
Indicates that one entity is directed toward, aimed at, or intended to affect another specific entity as its target.
-
C.
primaryTargetType
Indicates the main category or type of entity that is the principal focus or intended recipient of an action, effect, or operation.
-
D.
usedInType
Indicates that something serves as a component, element, or example within a particular type or category.
-
E.
haveType
Indicates that an entity belongs to or is classified under a specified type or category.
- 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_69a494060e148190abb42f971242c197 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bcaf3a9081908bad2eba74dffbc1 |
completed | March 1, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69a4bb525b648190adcb7a29256d3c41 |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:45 p.m.