Triple
T28754482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gongsun Zan |
E731628
|
entity |
| Predicate | diedInConflictWith |
P165284
|
FINISHED |
| Object | Yuan Shao |
—
|
NE NERFINISHED |
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: Yuan Shao | Statement: [Gongsun Zan, diedInConflictWith, Yuan Shao]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: diedInConflictWith Context triple: [Gongsun Zan, diedInConflictWith, Yuan Shao]
-
A.
diedInConflict
Indicates that an entity lost their life as a direct result of a specific conflict or war.
-
B.
conflictOfDeath
Indicates a relationship where a death occurs as a result of, or in the context of, an armed conflict or war.
-
C.
diedFor
Indicates that one entity’s death occurred as a sacrifice or in order to benefit, save, or serve another entity.
-
D.
killedInAttack
Indicates that an entity died as a direct result of a specific attack event.
-
E.
hasBurialsFromConflict
Indicates that the subject location or site contains burials that originated as a result of a specific conflict or violent event.
- 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_69f043ed68a881909e858a06bab7a247 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f657f9d5248190b6f3f82f20f069a3 |
completed | May 2, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69f651ada6048190a7b4a6981565dc3a |
completed | May 2, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69f6562ef4e4819082ce6abd41b74dc5 |
completed | May 2, 2026, 7:53 p.m. |
Created at: April 28, 2026, 6:09 a.m.