Triple
T17533139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terry Molloy |
E426987
|
entity |
| Predicate | notableCharacter |
P1481
|
FINISHED |
| Object | Mike Tucker |
—
|
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: Mike Tucker | Statement: [Terry Molloy, notableCharacter, Mike Tucker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mike Tucker Context triple: [Terry Molloy, notableCharacter, Mike Tucker]
-
A.
Mike Tucker
chosen
Mike Tucker is a fictional character from the long-running British science fiction television series "Doctor Who."
-
B.
Joe Renzetti
Joe Renzetti is an American composer best known for his film scores, particularly in the horror genre.
-
C.
Mike Malloy
Mike Malloy is a progressive American radio talk show host known for his outspoken, left-leaning political commentary and work on various liberal talk radio networks.
-
D.
Michael Tucker
Michael Tucker is an American television writer known for his work on the sitcom "Sorry."
-
E.
Michael Tucker
Michael Tucker, better known by his stage name BloodPop, is an American musician and record producer recognized for his work on numerous pop hits.
- 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_69d889de677081909b22d2657b1f0292 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4536a0f588190ade91d32308897a0 |
completed | April 19, 2026, 4 a.m. |
Created at: April 10, 2026, 5:49 a.m.