Triple
T19455690
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Damsel |
E486726
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object | Dan Mazeau |
—
|
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: Dan Mazeau | Statement: [Damsel, writer, Dan Mazeau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dan Mazeau Context triple: [Damsel, writer, Dan Mazeau]
-
A.
Dan Mazeau
chosen
Dan Mazeau is an American screenwriter known for working on major Hollywood action and fantasy films, including entries in the Fast & Furious franchise.
-
B.
Michael Malarkey
Michael Malarkey is a British-American actor and musician best known for his roles in television series such as The Vampire Diaries and historical dramas.
-
C.
Dan Mazer
Dan Mazer is a British screenwriter, director, and producer best known for his long-time collaboration with Sacha Baron Cohen on projects like Borat and Brüno.
-
D.
Dan Mahowny
Dan Mahowny is the central character in the film "Owning Mahowny," a bank employee whose secret, compulsive gambling habit drives him to commit large-scale financial fraud.
-
E.
Dave Morin
Dave Morin is an American entrepreneur and investor best known as a former Facebook executive and co-founder of the social networking startup Path.
- 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_69d8e8d86d608190bd199a98d0297f27 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e633c2b1108190b492ca23487b91f8 |
completed | April 20, 2026, 2:10 p.m. |
Created at: April 10, 2026, 1:38 p.m.