Triple
T12355453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States military tribunal for General Tomoyuki Yamashita |
E294599
|
entity |
| Predicate | sentenceMethod |
P859
|
FINISHED |
| Object | hanging |
—
|
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: hanging | Statement: [United States military tribunal for General Tomoyuki Yamashita, sentenceMethod, hanging]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sentenceMethod Context triple: [United States military tribunal for General Tomoyuki Yamashita, sentenceMethod, hanging]
-
A.
sentenceOf
Indicates that one entity is a sentence that belongs to, is contained in, or is part of another larger text or document.
-
B.
sentence
Indicates that one entity is a sentence that expresses, contains, or encodes information about another entity.
-
C.
sentenceType
Indicates the classification of a sentence according to its communicative function or structural type (e.g., question, statement, command).
-
D.
method
chosen
Indicates the technique, procedure, or process used by an entity to perform an action or achieve a result.
-
E.
sentenceModification
Indicates that one sentence alters, qualifies, or elaborates on the meaning, structure, or content of another sentence.
- 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_69d6ab6ccbec8190b09e2d357aa80064 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d942a2d6e08190a13c7ff89af09354 |
completed | April 10, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69d93ecf6b548190a394b6b56a0c1c68 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:54 p.m.