Triple
T18835257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Evans Behling |
E460647
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Michael Evans Behling |
—
|
NE NERFINISHED |
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: Michael Evans Behling | Statement: [Michael Evans Behling, name, Michael Evans Behling]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Evans Behling Context triple: [Michael Evans Behling, name, Michael Evans Behling]
-
A.
Michael Evans Behling
chosen
Michael Evans Behling is an American actor best known for his role as Jordan Baker on the television drama series "All American."
-
B.
Michael Begler
Michael Begler is an American television writer and producer best known for co-creating the period medical drama series "The Knick."
-
C.
John Eisendrath
John Eisendrath is a television writer and producer best known for his work on series such as "The Blacklist" and "Alias."
-
D.
Michael Lynn Evans III
Michael Lynn Evans III is an American professional football wide receiver best known for his standout career with the Tampa Bay Buccaneers in the NFL.
-
E.
Michael Thiel
Michael Thiel is an individual notable enough to be specifically distinguished from others sharing the surname Thiel.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dcfa11e4819090ab1ef5bdcd2b2e |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5a99d491c81909d8e55ac45621d44 |
completed | April 20, 2026, 4:20 a.m. |
Created at: April 10, 2026, 11:56 a.m.