Triple
T32900336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Willem Dafoe as John Clark |
E841589
|
entity |
| Predicate | primarySettingOfFilm |
P52439
|
FINISHED |
| Object | United States |
E14
|
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: United States | Statement: [Willem Dafoe as John Clark, primarySettingOfFilm, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primarySettingOfFilm Context triple: [Willem Dafoe as John Clark, primarySettingOfFilm, United States]
-
A.
primaryActivityInFilm
Indicates that an entity’s main or most significant activity, role, or function occurs within the context of a particular film.
-
B.
primaryCinema
Indicates that one entity is the main or most significant cinema associated with another entity (such as a person, work, or event).
-
C.
primarySettingOf
Indicates that a location or context serves as the main or principal setting in which an entity (such as a story, event, or activity) takes place.
-
D.
filmSetting
chosen
Indicates the place, time, or environment in which the events of a film are set or take place.
-
E.
primarySetting
Indicates that one entity serves as the main or central location, context, or environment in which the other entity’s events or activities primarily take place.
- F. None of above.
Provenance (4 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_69f34945ae408190b72d8118c83beb77 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a34c662c1a4819091cf85baab249018 |
completed | June 19, 2026, 4:32 a.m. |
| PD | Predicate disambiguation | batch_6a0379f0cbe481909b4b8fc6cbe297f0 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:19 a.m.