Triple
T9058746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lost Highway |
E217068
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Howard Benson |
E635841
|
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: Howard Benson | Statement: [Lost Highway, producer, Howard Benson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Howard Benson Context triple: [Lost Highway, producer, Howard Benson]
-
A.
Howard Benson
chosen
Howard Benson is a Grammy-nominated American record producer known for his work with prominent rock and pop artists such as My Chemical Romance, Daughtry, and Kelly Clarkson.
-
B.
Chris Benson
Chris Benson is an actor known for his role in the romantic sports film "The Cutting Edge."
-
C.
Howard Bowen
Howard Bowen was an American economist and university administrator best known for pioneering the concept of corporate social responsibility in modern business ethics.
-
D.
Glenn Williamson
Glenn Williamson is a film producer known for his work on independent and character-driven movies, including the dark comedy-drama "Sunshine Cleaning."
-
E.
Doug Benson
Doug Benson is an American stand-up comedian, actor, and podcast host best known for his marijuana-themed humor and the podcast "Doug Loves Movies."
- 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_69ca83d4425481909a319dab847724ec |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc7ec924f481908ca2eac98c68a41d |
completed | April 1, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfebe40ec08190a1da2aa1c6577723 |
completed | April 3, 2026, 4:33 p.m. |
Created at: March 30, 2026, 7:10 p.m.