Triple
T28544103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Empress Wu |
E722381
|
entity |
| Predicate | predecessorAsPrincipalWife |
P180223
|
FINISHED |
| Object | Lady Gan |
—
|
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: Lady Gan | Statement: [Empress Wu, predecessorAsPrincipalWife, Lady Gan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: predecessorAsPrincipalWife Context triple: [Empress Wu, predecessorAsPrincipalWife, Lady Gan]
-
A.
predecessorAsGreatRoyalWife
Indicates that one entity previously held the role of Great Royal Wife immediately before the other entity.
-
B.
predecessorAsQueenConsort
Indicates that one queen consort held the position immediately before another queen consort in a royal succession.
-
C.
predecessorAsEmpressConsort
Indicates that one empress consort held the position immediately before another empress consort in a succession.
-
D.
predecessorAsQueen
Indicates that one entity previously held the position of queen immediately before another entity.
-
E.
predecessorAsDuchessConsort
Indicates that one entity previously held the role of duchess consort immediately before another entity in a succession.
- 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_69f01a5e42348190b1ffbca26e739c84 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f739a638748190808e7a2930dce16e |
completed | May 3, 2026, 12:03 p.m. |
| PD | Predicate disambiguation | batch_69f732f2dc6c8190a4e86da98cc5eb05 |
completed | May 3, 2026, 11:35 a.m. |
| PDg | Predicate description generation | batch_69f739a58b3c81908abc2b8738a65678 |
completed | May 3, 2026, 12:03 p.m. |
Created at: April 28, 2026, 3:37 a.m.