Triple
T13941423
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Segal |
E335261
|
entity |
| Predicate | directed |
P7373
|
FINISHED |
| Object | Anger Management |
E392952
|
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: Anger Management | Statement: [Peter Segal, directed, Anger Management]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anger Management Context triple: [Peter Segal, directed, Anger Management]
-
A.
Anger Management
Anger Management is a record label known for producing and releasing music, including works such as La Rumba.
-
B.
Anger Management
chosen
Anger Management is a 2003 comedy film starring Adam Sandler and Jack Nicholson about a mild-mannered man forced into an unconventional and escalating course of anger management therapy.
-
C.
Anger Management
Anger Management is an American television sitcom starring Charlie Sheen as a non-traditional therapist with anger issues of his own.
-
D.
Anger
Anger is a municipality in the Bavarian Alps of southeastern Germany, known for its scenic landscapes and traditional rural character.
-
E.
Anger
Anger is one of the core emotion characters in Pixar's Inside Out films, embodying fiery frustration and outrage within the mind of the protagonist.
- 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_69d81c6081b88190b53e317c3370c8fe |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2cf6e29881908ddb8efca9a456a3 |
completed | April 14, 2026, 12:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7ce8bbd8c819084703298ed6d9c87 |
completed | May 3, 2026, 10:39 p.m. |
Created at: April 9, 2026, 10:17 p.m.