Triple
T30469385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Constance of Burgundy |
E775247
|
entity |
| Predicate | spouseOfMonarchOf |
P88104
|
FINISHED |
| Object | Kingdom of León |
—
|
NE NERFINISHED |
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: Kingdom of León | Statement: [Constance of Burgundy, spouseOfMonarchOf, Kingdom of León]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseOfMonarchOf Context triple: [Constance of Burgundy, spouseOfMonarchOf, Kingdom of León]
-
A.
spouseIsMonarchOf
chosen
Indicates that a person's spouse holds the position of monarch (ruler) of a specified country or territory.
-
B.
spouseOfHeirToThrone
Indicates that one person is the married partner of an individual who is the heir to a throne.
-
C.
spouseServedMonarch
Indicates that the spouse of a person held a position of service or duty to a monarch.
-
D.
marriedToMonarchFrom
Indicates that a person is married to a monarch who rules or comes from a specified country or region.
-
E.
regentSpouse
Indicates that one person is the spouse of a regent, i.e., married to an individual who rules on behalf of a monarch or in place of the sovereign.
- 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_69f2249622a48190b1fae2e3e4ee958a |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fcef654d588190b29ecc76678d1aa0 |
completed | May 7, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69fcecdb97f48190b382b7d13be92dc0 |
completed | May 7, 2026, 7:49 p.m. |
Created at: April 29, 2026, 8:11 p.m.