Triple
T16776610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Empress Dowager Xiaoding |
E407739
|
entity |
| Predicate | successorAsPrimaryConsortOfLongqing |
P124589
|
FINISHED |
| Object | none |
—
|
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: none | Statement: [Empress Dowager Xiaoding, successorAsPrimaryConsortOfLongqing, none]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: successorAsPrimaryConsortOfLongqing Context triple: [Empress Dowager Xiaoding, successorAsPrimaryConsortOfLongqing, none]
-
A.
successorAsEmpress
Indicates that one person became the next empress following another, directly succeeding her in that imperial role.
-
B.
successorAsChiefImperialLady
Indicates that one person becomes the next holder of the position of Chief Imperial Lady after another person.
-
C.
successorAsQueen
Indicates that one entity became queen directly after another, inheriting the queenship as her successor.
-
D.
successorAsQueenMother
Indicates that one individual assumed the role of Queen Mother directly after another individual, succeeding her in that specific position.
-
E.
predecessorAsEmpressConsort
Indicates that one empress consort held the position immediately before another empress consort 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_69d8839270588190886720d9519bbf8f |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b03a646c8190b3944c9f0c25af27 |
completed | April 18, 2026, 4:24 p.m. |
| PD | Predicate disambiguation | batch_69e319cf691c819083e39225f5777ef0 |
completed | April 18, 2026, 5:42 a.m. |
| PDg | Predicate description generation | batch_69e326bac94481908c082117553320f8 |
completed | April 18, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:22 a.m.