Triple
T3672942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rushmore |
E77920
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Barry Mendel |
E271299
|
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: Barry Mendel | Statement: [Rushmore, producer, Barry Mendel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barry Mendel Context triple: [Rushmore, producer, Barry Mendel]
-
A.
Barry Mendel
chosen
Barry Mendel is an American film producer known for acclaimed movies such as "The Sixth Sense," "Rushmore," and "Bridesmaids."
-
B.
Dan Grossman
Dan Grossman is a computer scientist and professor known for his work in programming languages and software engineering.
-
C.
David Bartel
David Bartel is an American molecular biologist known for his pioneering research on microRNAs and RNA interference in gene regulation.
-
D.
Michael Neeleman
Michael Neeleman is a notable individual recognized as a bearer of the Neeleman surname, likely distinguished in a professional or public context.
-
E.
Andy Lassner
Andy Lassner is a television producer best known for his long-running work on "The Ellen DeGeneres Show" and other major daytime talk shows.
- 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_69ad85e083008190b2e1b7085fe500bd |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc42f82548190b4d5f0fe7250decb |
completed | March 8, 2026, 6:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b48854a2308190ba6a9fc39929b35c |
completed | March 13, 2026, 9:57 p.m. |
Created at: March 8, 2026, 3:25 p.m.