Triple
T18078488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Archer |
E432622
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Mary Archer |
—
|
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: Mary Archer | Statement: [Mary Archer, name, Mary Archer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mary Archer Context triple: [Mary Archer, name, Mary Archer]
-
A.
Mary Archer
chosen
Mary Archer is a British scientist and academic, known for her work in solar energy research and for being married to novelist and former politician Jeffrey Archer.
-
B.
Anne Archer
Anne Archer is an American actress best known for her Academy Award–nominated role in the 1987 thriller "Fatal Attraction."
-
C.
Amy Archer
Amy Archer is a fast-talking, sharp-witted investigative reporter in the film "The Hudsucker Proxy" who uncovers corporate corruption.
-
D.
Marian McAlpin
Marian McAlpin is the conflicted young protagonist of Margaret Atwood’s novel "The Edible Woman," whose growing aversion to food mirrors her anxiety about identity, gender roles, and societal expectations.
-
E.
Sarah Davenport
Sarah Davenport was the wife of colonial American Congregational minister and educator Eleazar Wheelock, founder of Dartmouth College.
- 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_69d8b9070cac81909fa9473fb1c3f1c7 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4d9f6a85481909894c39c8be98d5d |
completed | April 19, 2026, 1:34 p.m. |
Created at: April 10, 2026, 10:27 a.m.