Triple
T37354387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tarek El Moussa |
E927413
|
entity |
| Predicate | marriageStartWithHeatherRaeElMoussa |
P195879
|
FINISHED |
| Object | 2021 |
—
|
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: 2021 | Statement: [Tarek El Moussa, marriageStartWithHeatherRaeElMoussa, 2021]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriageStartWithHeatherRaeElMoussa Context triple: [Tarek El Moussa, marriageStartWithHeatherRaeElMoussa, 2021]
-
A.
marriageStartWithMirraAlfassa
Indicates the event or point in time when a marriage begins in connection with Mirra Alfassa.
-
B.
marriageStartWithCaitlinMcHugh
Indicates the point in time when an individual begins a marital relationship with Caitlin McHugh.
-
C.
marriageToNadiaSawalha
Indicates a marital relationship in which the subject is married to Nadia Sawalha.
-
D.
marriageStartWithMilaKunis
Indicates the point in time when a marriage involving Mila Kunis begins.
-
E.
marriageStartWithHilaryBonner
Indicates the point in time when a person begins a marital relationship with Hilary Bonner.
- F. None of above. chosen
Provenance (4 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_69f76eb5e034819088e53ab5b7909a68 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fdec5ffe088190ac5505f26c6cff18 |
completed | May 8, 2026, 2 p.m. |
| PD | Predicate disambiguation | batch_69fdeae15f1c81908fc63fbc1b028d2e |
completed | May 8, 2026, 1:53 p.m. |
| PDg | Predicate description generation | batch_69fdec5f0420819087c0230ad384c4ba |
completed | May 8, 2026, 1:59 p.m. |
Created at: May 3, 2026, 4:16 p.m.