Triple
T29409610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jiang Wei |
E745857
|
entity |
| Predicate | predecessorAsChiefStrategist |
P181749
|
FINISHED |
| Object | Zhuge Liang |
—
|
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: Zhuge Liang | Statement: [Jiang Wei, predecessorAsChiefStrategist, Zhuge Liang]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: predecessorAsChiefStrategist Context triple: [Jiang Wei, predecessorAsChiefStrategist, Zhuge Liang]
-
A.
predecessorCEO
Indicates that one person previously held the position of CEO before another specific person.
-
B.
predecessorAsCommander
Indicates that one entity previously held the role of commander before another entity in the same command position.
-
C.
predecessorName
Indicates that the value is the name of an entity that directly precedes another in an ordered sequence or lineage.
-
D.
predecessorAsTreasurer
Indicates that one entity previously held the role of treasurer before another entity, establishing a predecessor relationship in that office.
-
E.
predecessorAsChiefOfTheDefenceForce
Indicates that one entity previously held the position of Chief of the Defence Force immediately before the other entity.
- 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_69f0a79eb7d081908c67197a5f347e68 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f7824dc3f0819092a5102895b4a478 |
completed | May 3, 2026, 5:13 p.m. |
| PD | Predicate disambiguation | batch_69f780fc5ed88190b7200ee5a29940af |
completed | May 3, 2026, 5:08 p.m. |
| PDg | Predicate description generation | batch_69f7817c79e081908e685c48165e086b |
completed | May 3, 2026, 5:10 p.m. |
Created at: April 28, 2026, 2:56 p.m.