Triple
T27487907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Empress Yin Lihua |
E693793
|
entity |
| Predicate | knownInHistoryAs |
P168596
|
FINISHED |
| Object | a model of virtuous empress |
—
|
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: a model of virtuous empress | Statement: [Empress Yin Lihua, knownInHistoryAs, a model of virtuous empress]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: knownInHistoryAs Context triple: [Empress Yin Lihua, knownInHistoryAs, a model of virtuous empress]
-
A.
historicalFigure
Indicates that an entity is recognized as a notable person from the past who played a significant role in history.
-
B.
roleInHistoryOf
Indicates that one entity holds a specific role, contribution, or significance within the historical development or narrative of another entity.
-
C.
notableHistoricalEntity
Indicates that an entity holds recognized historical significance or prominence within a historical context.
-
D.
historicalFigureAssociated
Indicates that there is a notable connection or linkage between an entity and a historical figure, such as influence, collaboration, representation, or involvement in the figure’s life or legacy.
-
E.
historicalPeople
Indicates that the related entities are people who lived in or are associated with a past historical period or context.
- 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_69ef5382b9648190be0b1ef2ad5d043c |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69f67595fa7c8190b6e9f7a8c700dd97 |
completed | May 2, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69f673c2f81c8190bf369226306eef09 |
completed | May 2, 2026, 9:59 p.m. |
| PDg | Predicate description generation | batch_69f674df80b08190adb7f7531083bbb1 |
completed | May 2, 2026, 10:04 p.m. |
Created at: April 27, 2026, 1:03 p.m.