Triple
T790933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chinese 87th Division |
E16911
|
entity |
| Predicate | statusDuringWar |
P19322
|
FINISHED |
| Object | frontline unit in early campaigns |
—
|
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: frontline unit in early campaigns | Statement: [Chinese 87th Division, statusDuringWar, frontline unit in early campaigns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: statusDuringWar Context triple: [Chinese 87th Division, statusDuringWar, frontline unit in early campaigns]
-
A.
enemyDuringWar
Indicates that one entity is an enemy of another specifically in the context of a particular war or armed conflict.
-
B.
legalStatusAfterWar
Indicates the legal condition or classification assigned to an entity as a consequence of, or following the conclusion of, a war or armed conflict.
-
C.
seatDuringWar
Indicates that an entity holds or occupies a seat, position, or place during a time of war or armed conflict.
-
D.
beganDuringConflict
Indicates that the action or relationship started while a specified conflict was ongoing.
-
E.
statusDuringColdWar
Indicates the political or diplomatic status or alignment that an entity held specifically during the Cold War period.
- 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_69a4936cb7448190914f5fe4b8d81607 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a79754988190ab494b1c54d6a2a4 |
completed | March 1, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69a4a50ef72c819084ffe9f31dbd0262 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a62b497081909503c8d30c7ce1db |
completed | March 1, 2026, 8:48 p.m. |
Created at: March 1, 2026, 7:38 p.m.