Triple
T777283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mao Anqing |
E16414
|
entity |
| Predicate | survivedSecondSinoJapaneseWar |
P19667
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Mao Anqing, survivedSecondSinoJapaneseWar, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: survivedSecondSinoJapaneseWar Context triple: [Mao Anqing, survivedSecondSinoJapaneseWar, true]
-
A.
sideInWorldWarII
Indicates that an entity was aligned with or participated on a particular side during World War II.
-
B.
postwarOutcome
Indicates the result or consequences that follow for a party or situation after a war has ended.
-
C.
worldWar
Indicates a large-scale armed conflict involving multiple nations across different regions of the world, typically encompassing numerous battles, alliances, and theaters of war.
-
D.
majorWar
Indicates a large-scale, intense armed conflict between major powers or involving substantial military forces and widespread impact.
-
E.
statusAfterWWII
Indicates the condition, role, or classification an entity had following the end of World War II.
- 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_69a4936ad1fc81908f190208059ccf78 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a74da7648190adfad56717d564df |
completed | March 1, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69a4a50a443481909ae3662764ee69a4 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a74c81bc81909f4ac9c1677b09c2 |
completed | March 1, 2026, 8:53 p.m. |
Created at: March 1, 2026, 7:37 p.m.