Triple
T14526959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Les Clark |
E340803
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Les Clark |
E340803
|
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: Les Clark | Statement: [Les Clark, name, Les Clark]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Les Clark Context triple: [Les Clark, name, Les Clark]
-
A.
Les Clark
chosen
Les Clark was an American animator and one of Disney’s famed "Nine Old Men," known for his influential work on many classic Disney films.
-
B.
Matt Clark
Matt Clark was an American character actor known for his numerous supporting roles in Westerns and other films and television series from the 1960s onward.
-
C.
Mike E. Clark
Mike E. Clark is an American record producer best known for his long-running work with Insane Clown Posse and other artists on the Psychopathic Records label.
-
D.
Louis Clark
Louis Clark was an English arranger and conductor best known for orchestrating and conducting the string arrangements for Electric Light Orchestra and later leading the Hooked on Classics series.
-
E.
Tim Clark
Tim Clark is a British airline executive best known as the longtime president of Emirates, where he played a key role in transforming it into a major global carrier.
- 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_69d822dac79c8190a84a073f3cbaced5 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dea050781881909ed685d94479bf99 |
completed | April 14, 2026, 8:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd8ab24f8c8190bb0e68ebb854844d |
completed | May 8, 2026, 7:03 a.m. |
Created at: April 10, 2026, 1:22 a.m.