Triple
T1417157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | International Military Tribunal for the Far East |
E31942
|
entity |
| Predicate | numberAcquitted |
P5674
|
FINISHED |
| Object | 0 |
—
|
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: 0 | Statement: [International Military Tribunal for the Far East, numberAcquitted, 0]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberAcquitted Context triple: [International Military Tribunal for the Far East, numberAcquitted, 0]
-
A.
numberOfAcquittals
chosen
Indicates the count of instances in which an entity has been formally acquitted of charges or accusations.
-
B.
acquittedBy
Indicates that an entity was formally cleared of charges or blame through a decision or judgment made by another entity.
-
C.
acquittedOf
Indicates that an authority has formally cleared an entity of a specific charge, accusation, or wrongdoing.
-
D.
numberOfPeopleAccused
Indicates the count of individuals who are formally alleged to have committed a particular act or offense.
-
E.
numberOfConvictions
Indicates the count of times an entity has been formally found guilty of an offense.
- 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_69a49919a994819086528951bc224775 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c403ccdc8190b2a5fda037b6ea34 |
completed | March 1, 2026, 10:56 p.m. |
| PD | Predicate disambiguation | batch_69a4bf060b0081909ba00e6ac093a28b |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:59 p.m.