Triple
T7740585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Margaret Hooper Mahon |
E175496
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Margaret Hooper Mahon |
E175496
|
NE 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: Margaret Hooper Mahon | Statement: [Margaret Hooper Mahon, name, Margaret Hooper Mahon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Margaret Hooper Mahon Context triple: [Margaret Hooper Mahon, name, Margaret Hooper Mahon]
-
A.
Margaret Hooper Mahon
chosen
Margaret Hooper Mahon was the wife of Canadian medical scientist Charles Best, who co-discovered insulin.
-
B.
Margaret Kelly
Margaret Kelly is an American artist and the first wife of actor and comedian Bill Murray, to whom she was married from 1981 to 1996.
-
C.
Margaret Hartnett
Margaret Hartnett is a person notable enough to be recognized as a significant bearer of the surname Hartnett.
-
D.
Margaret Hitchcock Doorly
Margaret Hitchcock Doorly was a prominent Omaha philanthropist whose support and legacy led to the city’s renowned Henry Doorly Zoo and Aquarium bearing her name.
-
E.
Margaret Davenport
Margaret Davenport is the mother of American actor Emile Hirsch.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c6995f9c60819092e386192bd63c6f |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7035cddb881908bdfc1bd7d6a64ad |
completed | March 27, 2026, 10:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8be4178408190850c284aab895442 |
completed | March 29, 2026, 5:53 a.m. |
Created at: March 27, 2026, 4:07 p.m.