Triple
T24749051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stacia Robitaille |
E619085
|
entity |
| Predicate | marriedToSportsFigure |
P136969
|
FINISHED |
| Object | Luc Robitaille |
—
|
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: Luc Robitaille | Statement: [Stacia Robitaille, marriedToSportsFigure, Luc Robitaille]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriedToSportsFigure Context triple: [Stacia Robitaille, marriedToSportsFigure, Luc Robitaille]
-
A.
spouseOfSportsFigure
chosen
Indicates a marital relationship where one person is the spouse of a sports figure.
-
B.
spouseSport
Indicates that the sport is the one played or practiced by a person's spouse.
-
C.
marriedToNotablePerson
Indicates that a person is legally married to another individual who is widely recognized or notable.
-
D.
marriedToBeforeFameOf
Indicates that one person was married to another person before the latter became famous.
-
E.
hasPublicFigureSpouse
Indicates that a person’s spouse is a public figure, such as a celebrity, politician, or other widely recognized individual.
- 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_69e2fabb349881908a13a212a0221a63 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f410a25ab88190a72db43043c1f6ff |
completed | May 1, 2026, 2:32 a.m. |
| PD | Predicate disambiguation | batch_69f40ef612c88190ab2f3f08d4a92018 |
completed | May 1, 2026, 2:24 a.m. |
Created at: April 18, 2026, 4:24 a.m.