Triple
T30059205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maureen Starkey Tigrett |
E763822
|
entity |
| Predicate | marriageEndWithIsaacTigrett |
P181151
|
FINISHED |
| Object | 1994 |
—
|
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: 1994 | Statement: [Maureen Starkey Tigrett, marriageEndWithIsaacTigrett, 1994]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriageEndWithIsaacTigrett Context triple: [Maureen Starkey Tigrett, marriageEndWithIsaacTigrett, 1994]
-
A.
marriageStartWithIsaacTigrett
Indicates the event or point in time when a marriage begins that involves Isaac Tigrett as one of the spouses.
-
B.
marriageEndTimeWithRossKemp
Indicates the time at which a marriage involving Ross Kemp officially ended.
-
C.
marriageEndWithElizabethTaylor
Indicates that a marriage concluded with Elizabeth Taylor as one of the spouses.
-
D.
marriageEndToKateCapshaw
Indicates that a marriage relationship has ended with Kate Capshaw as one of the spouses.
-
E.
marriageEndTimeWithCharityHallett
Indicates the time at which a marriage involving Charity Hallett came to an end.
- 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_69f224716378819087a722e487832b70 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f7626667f48190ad90867eb67ec582 |
completed | May 3, 2026, 2:57 p.m. |
| PD | Predicate disambiguation | batch_69f76175d6608190b60b268e20f49ed9 |
completed | May 3, 2026, 2:53 p.m. |
| PDg | Predicate description generation | batch_69f762651e088190baa21f25378a6065 |
completed | May 3, 2026, 2:57 p.m. |
Created at: April 29, 2026, 6:57 p.m.