Triple
T15600296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Halloween II |
E375012
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object | Debra Hill |
E285696
|
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: Debra Hill | Statement: [Halloween II, writer, Debra Hill]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Debra Hill Context triple: [Halloween II, writer, Debra Hill]
-
A.
Debra Hill
chosen
Debra Hill was an American film producer and screenwriter best known for co-writing and producing influential horror films such as "Halloween" alongside John Carpenter.
-
B.
Diane Chambers
Diane Chambers is an intelligent, sophisticated, and often pretentious waitress and love interest of Sam Malone on the classic American sitcom "Cheers."
-
C.
Debbie Aldridge
Debbie Aldridge is a fictional character from the long-running BBC Radio 4 soap opera "The Archers."
-
D.
Debbie Edwards
Debbie Edwards is the kidnapped niece whose years-long search drives the emotional core of John Ford’s classic Western film "The Searchers."
-
E.
Debralee Scott
Debralee Scott was an American actress best known for her comedic roles on 1970s and 1980s television sitcoms and films.
- 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_69d85cce25008190b13b52745fbd719b |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e621fc4819097e8e85e7ddfdc6c |
completed | April 16, 2026, 2:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff997b9c9081908f6a68e28a50a359 |
completed | May 9, 2026, 8:30 p.m. |
Created at: April 10, 2026, 4:12 a.m.