Triple
T12605026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fail Safe |
E300954
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Hildy Parks |
E536067
|
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: Hildy Parks | Statement: [Fail Safe, castMember, Hildy Parks]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hildy Parks Context triple: [Fail Safe, castMember, Hildy Parks]
-
A.
Hildy Parks
chosen
Hildy Parks was an American actress and television writer known for her work on stage, screen, and in creating and writing award shows.
-
B.
Hildy Brooks
Hildy Brooks is an American actress known for her work in film and television, including a role in the adaptation of Chaim Potok’s novel "The Chosen."
-
C.
Hildy Johnson
Hildy Johnson is the fast-talking, ambitious newspaper reporter at the center of the classic newsroom comedy "The Front Page."
-
D.
Hildy Beyeler
Hildy Beyeler is a Swiss art patron known for co-founding the renowned Beyeler Foundation Museum, which houses one of Europe’s leading collections of modern and contemporary art.
-
E.
Hildy
Hildy is a brash, fast-talking New York City taxi driver and one of the central comic female leads in the musical "On the Town."
- 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_69d7bdea2ca881908f379526c13b1145 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954e7f2dc8190a42cab7a0e5ea7f3 |
completed | April 10, 2026, 7:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65ecd1b748190bd961497b30e1ae5 |
completed | May 2, 2026, 8:30 p.m. |
Created at: April 9, 2026, 5:10 p.m.