Triple
T24058624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Empress Xiaoquancheng |
E595878
|
entity |
| Predicate | enteredHaremOf |
P154701
|
FINISHED |
| Object | Daoguang Emperor |
—
|
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: Daoguang Emperor | Statement: [Empress Xiaoquancheng, enteredHaremOf, Daoguang Emperor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: enteredHaremOf Context triple: [Empress Xiaoquancheng, enteredHaremOf, Daoguang Emperor]
-
A.
enteredInto
Indicates that one entity has initiated or become formally involved in a particular state, agreement, relationship, or situation with another entity.
-
B.
positionInHarem
Indicates the rank or hierarchical standing that an individual holds within a harem.
-
C.
enteredIntoBy
Indicates that an agreement, contract, or formal arrangement has been initiated or established by a particular party.
-
D.
enteredConvent
Indicates that a person has joined and been admitted into a religious convent as a member.
-
E.
intrudedInto
Indicates that one entity has entered or encroached upon another entity’s space, domain, or context without permission or in an unwelcome manner.
- 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_69e288c184b081909f1f1751fb8e299a |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1da52b9d48190b503fad5ff70e4c6 |
completed | April 29, 2026, 10:15 a.m. |
| PD | Predicate disambiguation | batch_69f1764b1d4c8190b12590c6339c31c1 |
completed | April 29, 2026, 3:08 a.m. |
| PDg | Predicate description generation | batch_69f1785afe3c81909be28986ffe944bf |
completed | April 29, 2026, 3:17 a.m. |
Created at: April 17, 2026, 10:36 p.m.