Triple
T8361725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duel (teleplay) |
E197022
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | David Mann |
E729012
|
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: David Mann | Statement: [Duel (teleplay), mainCharacter, David Mann]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: David Mann Context triple: [Duel (teleplay), mainCharacter, David Mann]
-
A.
David Mann
chosen
David Mann is the harried, everyman motorist relentlessly terrorized by a mysterious truck driver in Steven Spielberg’s thriller film "Duel."
-
B.
David Mann
David Mann is an American actor and comedian best known for his recurring roles in Tyler Perry’s stage plays and films, particularly as the character Mr. Brown.
-
C.
Robert Mann
Robert Mann was a 19th-century American man best known as the son of influential education reformer Horace Mann.
-
D.
Don Hahn
Don Hahn is an American film producer best known for overseeing several of Disney’s most acclaimed animated features, including Beauty and the Beast and The Lion King.
-
E.
Hank Corwin
Hank Corwin is an acclaimed American film editor known for his impressionistic, nonlinear cutting style on films such as The Tree of Life, The Big Short, and Vice.
- 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_69ca82f2dbe48190aba982e75a0d94de |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb8074e4588190b394d1622adca2cb |
completed | March 31, 2026, 8:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cde7c747b48190b1979b4eaf281df5 |
completed | April 2, 2026, 3:51 a.m. |
Created at: March 30, 2026, 6 p.m.