Triple
T33296790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Samuel Loomis (Halloween 2007) |
E852468
|
entity |
| Predicate | filmReleaseYearOfSecondAppearance |
P125091
|
FINISHED |
| Object | 2009 |
—
|
LITERAL 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: 2009 | Statement: [Dr. Samuel Loomis (Halloween 2007), filmReleaseYearOfSecondAppearance, 2009]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmReleaseYearOfSecondAppearance Context triple: [Dr. Samuel Loomis (Halloween 2007), filmReleaseYearOfSecondAppearance, 2009]
-
A.
yearOfFilmAppearance
Indicates the specific year in which a film appearance by an entity took place.
-
B.
workReleaseYearOfAppearance
Indicates the year in which a particular work was first released or made its initial appearance.
-
C.
secondAppearanceYear
chosen
Indicates the year in which an entity made its second appearance or occurrence.
-
D.
comicReleaseYear
Indicates the year in which a comic was first released or published.
-
E.
filmReleaseYear
Indicates the calendar year in which a film was first officially released to the public.
- F. None of above.
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_69f34966ed4c81908dc9dda82d8c7fe3 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6f38159d08190980ad639e08f00f4 |
completed | May 3, 2026, 7:04 a.m. |
| PD | Predicate disambiguation | batch_69f6e3d7bee48190b94e0beb48a1d7fa |
completed | May 3, 2026, 5:57 a.m. |
Created at: May 1, 2026, 1:33 a.m.