Triple
T13146239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Zellner |
E312341
|
entity |
| Predicate | directorOf |
P537
|
FINISHED |
| Object | Damsel |
E1024367
|
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: Damsel | Statement: [David Zellner, directorOf, Damsel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Damsel Context triple: [David Zellner, directorOf, Damsel]
-
A.
Damsel
Damsel is a 2024 dark fantasy adventure film starring Millie Bobby Brown as a princess who must fight for survival after being sacrificed to a dragon.
-
B.
Damsel
chosen
Damsel is a 2018 offbeat Western dark comedy film directed by David and Nathan Zellner, starring Robert Pattinson and Mia Wasikowska.
-
C.
Enchant
Enchant is an American progressive rock band known for its melodic, guitar-driven sound and intricate song structures.
-
D.
Damsels in Distress
Damsels in Distress is a 2011 indie comedy film written and directed by Whit Stillman that follows a group of college women attempting to improve their campus’s social life and mental health culture.
-
E.
The Girl
The Girl is a mysterious, supernatural woman in the film "The Ninth Gate" who guides and manipulates the protagonist as he investigates a demonic book.
- 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_69d806aabde48190899e13e41659cae5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98bcf6d0c819081d078f33e4bdedc |
completed | April 10, 2026, 11:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6f5da0f708190b848601e571a9fff |
completed | May 3, 2026, 7:14 a.m. |
Created at: April 9, 2026, 9:10 p.m.