Triple
T14176916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clare Foley |
E351355
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Clare Foley |
E351355
|
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: Clare Foley | Statement: [Clare Foley, name, Clare Foley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Clare Foley Context triple: [Clare Foley, name, Clare Foley]
-
A.
Clare Foley
chosen
Clare Foley is an American actress known for her roles in film and television, including appearances in projects like the boxing drama "Southpaw" and the TV series "Gotham."
-
B.
Bridget Moynahan
Bridget Moynahan is an American actress and model best known for her roles in films like "Coyote Ugly" and "I, Robot" and the TV series "Blue Bloods."
-
C.
Rachel Kelley
Rachel Kelley was the mother of Jesse Root Grant and the paternal grandmother of U.S. President Ulysses S. Grant.
-
D.
Caitlin Leahy
Caitlin Leahy is an American actress and model known for her roles in film and television, including appearances in action and drama projects.
-
E.
Stephany Folsom
Stephany Folsom is an American screenwriter best known for co-writing Pixar’s animated film "Toy Story 4" and contributing to various high-profile film and television projects.
- 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_69d8278834a08190b0f1784e58d7b99c |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61c76e8081909994b95b631100e9 |
completed | April 14, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd7a2fdd7c8190b2ebf5a18c8039f2 |
completed | May 8, 2026, 5:52 a.m. |
Created at: April 10, 2026, 1:02 a.m.