Triple
T23337601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Empress Xiaojingcheng |
E591638
|
entity |
| Predicate | eraNameOfSpouse |
P151923
|
FINISHED |
| Object | Daoguang |
—
|
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 | Statement: [Empress Xiaojingcheng, eraNameOfSpouse, Daoguang]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eraNameOfSpouse Context triple: [Empress Xiaojingcheng, eraNameOfSpouse, Daoguang]
-
A.
spouseNameAtMarriage
Indicates the full name a person’s spouse had at the time of their marriage.
-
B.
spouseAlsoKnownAs
Indicates that a person’s spouse is referred to by an alternative name or alias.
-
C.
spouse name
Indicates that one entity is the legally recognized husband or wife of the other, specifying the partner’s name in a marital relationship.
-
D.
spouseBirthName
Indicates the birth name of a person's spouse, prior to any name changes such as through marriage.
-
E.
laterMarriedName
Indicates that the referenced name is a surname or full name a person adopted after a later marriage, replacing or succeeding their previous name.
- 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_69e25d20156c81908c5c53195bd9c738 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1982f8574819090f8b0ba249237a3 |
completed | April 29, 2026, 5:33 a.m. |
| PD | Predicate disambiguation | batch_69effcfd8d288190937a887fe6023c11 |
completed | April 28, 2026, 12:19 a.m. |
| PDg | Predicate description generation | batch_69f01d88b4ec8190a2a17a88e0eda178 |
completed | April 28, 2026, 2:38 a.m. |
Created at: April 17, 2026, 5:17 p.m.