Triple
T37427419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arieta |
E930029
|
entity |
| Predicate | spouseOrdinality |
P4764
|
FINISHED |
| Object | one of multiple wives of Ordoño II of León |
—
|
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: one of multiple wives of Ordoño II of León | Statement: [Arieta, spouseOrdinality, one of multiple wives of Ordoño II of León]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseOrdinality Context triple: [Arieta, spouseOrdinality, one of multiple wives of Ordoño II of León]
-
A.
spouseOrder
chosen
Indicates the position or sequence of a person among multiple spouses in a marital relationship.
-
B.
spouseOrdinalNumberAsPresident
Indicates the numerical order in which a person’s spouse served as president (e.g., first, second, third).
-
C.
motherSpouseOrder
Indicates that the subject is the spouse of the object’s mother, with an ordering or ranking among multiple such spouses.
-
D.
spouseOfSequence
Indicates a sequential or ordered relationship of being spouses, where each entity is married to the next in the sequence.
-
E.
spouseIn
Indicates that one entity is the spouse (married partner) of another entity within a specified context or grouping.
- 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_69f76ebf0f288190ba198a78341613b8 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69feba0f09508190b3e871c62b19ec7f |
completed | May 9, 2026, 4:37 a.m. |
| PD | Predicate disambiguation | batch_69feb957fe7c8190969fb31a6d1a59c8 |
completed | May 9, 2026, 4:34 a.m. |
Created at: May 3, 2026, 4:16 p.m.