Triple
T12998156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Halloween (Part 1) |
E322096
|
entity |
| Predicate | director |
P255
|
FINISHED |
| Object | David Semel |
E285843
|
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 Semel | Statement: [Halloween (Part 1), director, David Semel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: David Semel Context triple: [Halloween (Part 1), director, David Semel]
-
A.
David Semel
chosen
David Semel is an American television director and producer known for his work on numerous high-profile series, including serving as an executive producer on the adaptation of "The Man in the High Castle."
-
B.
Stephen Semel
Stephen Semel is an American film and television editor known for his work on various feature films and TV series.
-
C.
Henry Samueli
Henry Samueli is an American engineer, technology entrepreneur, and philanthropist best known as the co-founder of Broadcom Corporation and a prominent NHL team owner.
-
D.
Richard P. Levine
Richard P. Levine is a film producer best known for his work on the World War II epic "A Bridge Too Far."
-
E.
Frank Lanning
Frank Lanning was an American character actor of the silent film era, known for his supporting roles in numerous Westerns and early Hollywood productions.
- 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_69d8076479b8819090afce3591939cdf |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e7b268c8190b8bb855e9de23c3b |
completed | April 10, 2026, 10:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6c101ea60819098e4d5fb3a9e803a |
completed | May 3, 2026, 3:29 a.m. |
Created at: April 9, 2026, 8:46 p.m.