Triple
T12355132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States military tribunal in Manila |
E294591
|
entity |
| Predicate | sentenceInYamashitaCase |
P104726
|
FINISHED |
| Object | death |
—
|
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: death | Statement: [United States military tribunal in Manila, sentenceInYamashitaCase, death]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sentenceInYamashitaCase Context triple: [United States military tribunal in Manila, sentenceInYamashitaCase, death]
-
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.
JapaneseFormation
Indicates a relationship where something is formed, created, or organized according to Japanese style, methods, or origin.
-
E.
SakaeIs
Indicates that one entity is identified as or classified as "Sakae" in relation to another entity or context.
- 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_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. |
| PDg | Predicate description generation | batch_69d9429ff2bc8190b09adf8f57fad451 |
completed | April 10, 2026, 6:34 p.m. |
Created at: April 8, 2026, 9:54 p.m.