Triple
T1285227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tommy Mottola |
E27418
|
entity |
| Predicate | marriageStartWithThalía |
P23691
|
FINISHED |
| Object | 2000-12-02 |
—
|
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: 2000-12-02 | Statement: [Tommy Mottola, marriageStartWithThalía, 2000-12-02]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriageStartWithThalía Context triple: [Tommy Mottola, marriageStartWithThalía, 2000-12-02]
-
A.
hasMarriagePlot
Indicates that the work’s narrative centrally involves courtship, romantic relationships, or the progression toward marriage as a key plot element.
-
B.
ageAtMarriage
Indicates the age a person was when they got married.
-
C.
marries
chosen
Indicates that one entity enters into a legally or socially recognized marital union with another entity.
-
D.
marriageType
Indicates the specific legal or social category of a marriage relationship that exists between two spouses.
-
E.
marriedInto
Indicates that one entity became connected to another’s family or group through marriage, rather than by birth or prior membership.
- 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_69a496d4ec448190ad653b2590c46711 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c0b6dda48190a2e79084adea6ec1 |
completed | March 1, 2026, 10:41 p.m. |
| PD | Predicate disambiguation | batch_69a4bee276d8819092f71c5a1140bb61 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:51 p.m.