Triple
T16642852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Empress Xiaojing |
E404385
|
entity |
| Predicate | typeOfMonarchConsort |
P123691
|
FINISHED |
| Object | principal consort |
—
|
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: principal consort | Statement: [Empress Xiaojing, typeOfMonarchConsort, principal consort]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfMonarchConsort Context triple: [Empress Xiaojing, typeOfMonarchConsort, principal consort]
-
A.
monarchConsortOf
Indicates that one person is the spouse of a reigning monarch, holding the role of consort to that monarch.
-
B.
monarchOfConsort
Indicates that one entity is the consort (spouse) of the reigning monarch of another entity (typically a state or territory).
-
C.
spouseIsMonarchOf
Indicates that a person's spouse holds the position of monarch (ruler) of a specified country or territory.
-
D.
spouseOfHeirToThrone
Indicates that one person is the married partner of an individual who is the heir to a throne.
-
E.
siblingOrConsort
Indicates that two entities are related either as siblings (sharing at least one parent) or as consorts (spouses/partners in a marital or analogous union).
- 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_69d8838a41f08190b0c3f79c47df5078 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37ad27b5481908316b4f23fb8bc32 |
completed | April 18, 2026, 12:36 p.m. |
| PD | Predicate disambiguation | batch_69e296af2f88819092c9ffee4a65d7dd |
completed | April 17, 2026, 8:23 p.m. |
| PDg | Predicate description generation | batch_69e2d7fb02f481908885a226c2191231 |
completed | April 18, 2026, 1:01 a.m. |
Created at: April 10, 2026, 5:18 a.m.