Triple
T26131296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Burt |
E659253
|
entity |
| Predicate | marriedToRankOfSpouse |
P138446
|
FINISHED |
| Object | Prussian field marshal |
—
|
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: Prussian field marshal | Statement: [Mary Burt, marriedToRankOfSpouse, Prussian field marshal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriedToRankOfSpouse Context triple: [Mary Burt, marriedToRankOfSpouse, Prussian field marshal]
-
A.
marriedToRank
Indicates that one entity is married to another entity who holds a specific rank or position.
-
B.
hasSpouseMilitaryRank
chosen
Indicates that a person’s spouse holds a specific military rank.
-
C.
hasSpousePositionInFamily
Indicates that a person’s spouse holds a specific role or position within the family structure.
-
D.
spouseOfHead
Indicates that one person is the married partner of the individual who holds the position of head (e.g., head of a household, organization, or state).
-
E.
marriedBy
Indicates that one entity is the officiant or authority who performs and formalizes the marriage of another entity.
- 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_69ee5bc3c20c8190bf2cf272f4170e95 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f650c70d7c819093d9a0f005f7c8d5 |
completed | May 2, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69f64cab1f648190a2a9460690d18a37 |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 26, 2026, 8:15 p.m.