Triple
T4101279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Serenity (2019 film) |
E87945
|
entity |
| Predicate | cinematography |
P1953
|
FINISHED |
| Object | Jess Hall |
E322054
|
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: Jess Hall | Statement: [Serenity (2019 film), cinematography, Jess Hall]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jess Hall Context triple: [Serenity (2019 film), cinematography, Jess Hall]
-
A.
Jess Hall
chosen
Jess Hall is a British cinematographer known for his visually distinctive work on films such as "Transcendence," "Hot Fuzz," and "Ghost in the Shell."
-
B.
Jennifer Hall
Jennifer Hall is the daughter of acclaimed French-American actress and dancer Leslie Caron.
-
C.
Dick Hallorann
Dick Hallorann is the kindly, psychic cook who shares a telepathic "shining" with Danny Torrance and helps him survive the horrors of the Overlook Hotel in Stephen King's horror story.
-
D.
Jo Hayden
Jo Hayden is the ambitious young vaudeville singer portrayed by Judy Garland in the 1942 musical film "For Me and My Gal."
-
E.
Skip Hall
Skip Hall is an American politician who serves as the mayor of Surprise, Arizona.
- 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_69aed94564cc8190a9c1457daedb6e7f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefd0ed168819093c83ba079d6725c |
completed | March 9, 2026, 5:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b56b7833b081909bf5a87ee709b49f |
completed | March 14, 2026, 2:06 p.m. |
Created at: March 9, 2026, 3:40 p.m.