Triple
T29868700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Empress Guo |
E758526
|
entity |
| Predicate | nobleRankBeforeEmpress |
P31174
|
FINISHED |
| Object | Guiren (Noble Lady) |
—
|
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: Guiren (Noble Lady) | Statement: [Empress Guo, nobleRankBeforeEmpress, Guiren (Noble Lady)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nobleRankBeforeEmpress Context triple: [Empress Guo, nobleRankBeforeEmpress, Guiren (Noble Lady)]
-
A.
nobleRankAbove
chosen
Indicates that one entity holds a higher noble rank or title in a hierarchy than another entity.
-
B.
predecessorAsChiefImperialLady
Indicates that one entity previously held the position of chief imperial lady immediately before another entity.
-
C.
nobleRankGrantedBy
Indicates that a particular noble rank or title was formally conferred upon someone by a specific granting authority or person.
-
D.
realmAsEmpress
Indicates that an entity holds the position or role of empress over a specified realm or domain.
-
E.
predecessorAsEmpressConsort
Indicates that one empress consort held the position immediately before another empress consort in a succession.
- F. None of above.
Provenance (3 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_69f2245d0d7081909e37ee328542bcd7 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6768b2bf48190af4821d43d7ee766 |
completed | May 2, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69f66ec8298c8190b41fe9d182c05676 |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 29, 2026, 5:52 p.m.