Triple
T28745744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xiao Qiao |
E731366
|
entity |
| Predicate | roleInRomanceOfTheThreeKingdoms |
P197231
|
FINISHED |
| Object | wife of Wu general Zhou Yu |
—
|
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: wife of Wu general Zhou Yu | Statement: [Xiao Qiao, roleInRomanceOfTheThreeKingdoms, wife of Wu general Zhou Yu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInRomanceOfTheThreeKingdoms Context triple: [Xiao Qiao, roleInRomanceOfTheThreeKingdoms, wife of Wu general Zhou Yu]
-
A.
roleInMulan
Indicates that one entity has a specific role or part in the context of "Mulan" (such as the film, story, or production).
-
B.
roleInGenpeiWar
Indicates the specific role, position, or involvement an entity had in the events or factions of the Genpei War.
-
C.
ChineseCommander
Indicates that an individual holds a commander role within a Chinese military or armed forces context.
-
D.
roleInShu
Indicates that an entity holds or plays a specific role within the context of Shu (e.g., the state, domain, or system referred to as Shu).
-
E.
roleInRomeoAndJuliet
Indicates the specific character or part that an entity plays in the work "Romeo and Juliet."
- 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_69f043ecb5c081909ec9da1172d68ece |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69fe7eb4b8348190bb19d35766189ed4 |
completed | May 9, 2026, 12:24 a.m. |
| PD | Predicate disambiguation | batch_69fe7c35d2148190ab952e54feda1e76 |
completed | May 9, 2026, 12:13 a.m. |
| PDg | Predicate description generation | batch_69fe7eb31b04819081be531fd9f8a78c |
completed | May 9, 2026, 12:24 a.m. |
Created at: April 28, 2026, 6:05 a.m.