Triple
T17534743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jock Mahoney |
E427027
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Margaret Field |
—
|
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: Margaret Field | Statement: [Jock Mahoney, spouse, Margaret Field]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Margaret Field Context triple: [Jock Mahoney, spouse, Margaret Field]
-
A.
Margaret Field
chosen
Margaret Field was an American actress and the mother of Academy Award–winning actress Sally Field.
-
B.
Patricia Dainton
Patricia Dainton was a British film and television actress known for her roles in 1950s and 1960s thrillers and dramas.
-
C.
Catherine Blaiklock
Catherine Blaiklock is a British politician and businesswoman best known as the founder and first leader of the Brexit Party.
-
D.
Margaret Welsh
Margaret Welsh is an American actress known for her work in film, television, and theater.
-
E.
Margaret Neale
Margaret Neale is an American organizational behavior scholar and negotiation expert, best known as a longtime professor at Stanford Graduate School of Business.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889de677081909b22d2657b1f0292 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4536ac7f48190994f7b39a6a811d7 |
completed | April 19, 2026, 4 a.m. |
Created at: April 10, 2026, 5:49 a.m.