Triple
T9137312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel Francis Boyle |
E219234
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | 127 Hours |
E62150
|
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: 127 Hours | Statement: [Daniel Francis Boyle, notableWork, 127 Hours]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 127 Hours Context triple: [Daniel Francis Boyle, notableWork, 127 Hours]
-
A.
127 Hours
chosen
127 Hours is a biographical survival drama film directed by Danny Boyle that tells the true story of mountaineer Aron Ralston’s entrapment in a Utah canyon.
-
B.
The Impossible
The Impossible is a 2012 disaster drama film that recounts the true story of a family's struggle to survive and reunite in the aftermath of the 2004 Indian Ocean tsunami.
-
C.
Argo
Argo is the legendary ship of Greek mythology that carried Jason and the Argonauts on their quest for the Golden Fleece.
-
D.
Argo
Argo is a 2012 political thriller film directed by Ben Affleck that dramatizes a covert operation to rescue American hostages from Iran during the 1979–1981 crisis.
-
E.
Argo
Argo is a popular open-source suite of Kubernetes-native tools for running and managing container-native workflows, applications, and continuous delivery pipelines.
- 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_69ca83e012288190a5771058adbaabd2 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8e1dc208190aafe501374ffe65c |
completed | April 1, 2026, 5:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d047fb3c148190b2e1a19d4f76b550 |
completed | April 3, 2026, 11:06 p.m. |
Created at: March 30, 2026, 7:19 p.m.