Triple
T16027533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Empress Xiaojie |
E388755
|
entity |
| Predicate | consortRank |
P11700
|
FINISHED |
| Object | 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: empress | Statement: [Empress Xiaojie, consortRank, empress]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: consortRank Context triple: [Empress Xiaojie, consortRank, empress]
-
A.
notableConsort
Indicates that one entity is a spouse or consort of another who is notable or significant in some recognized context.
-
B.
possibleConsortOf
Indicates that one entity is a potential or likely romantic or marital partner of another, without asserting that the relationship is confirmed.
-
C.
marriedToRank
Indicates that one entity is married to another entity who holds a specific rank or position.
-
D.
associatedWithRank
chosen
Indicates a relationship where an entity is linked to a specific rank, level, or hierarchical position.
-
E.
hasConsortCrowned
Indicates that an individual has a spouse or consort who has been formally crowned, typically in a royal or ceremonial context.
- 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_69d86dada3808190825d5f80d72fbe88 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1858a00888190b8505071575dc56f |
completed | April 17, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e1826a4f7c8190aba6d4f1075141b0 |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 4:56 a.m.