Triple
T32456300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elizabeth Lucy |
E829434
|
entity |
| Predicate | hasAlternateTitleFilm |
P94897
|
FINISHED |
| Object | The Hooker Cult Murders |
—
|
NE NERFINISHED |
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: The Hooker Cult Murders | Statement: [Elizabeth Lucy, hasAlternateTitleFilm, The Hooker Cult Murders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlternateTitleFilm Context triple: [Elizabeth Lucy, hasAlternateTitleFilm, The Hooker Cult Murders]
-
A.
filmAlternateTitle
chosen
Indicates that a film is known or released under an alternative title.
-
B.
haveAlternativeTitle
Indicates that an entity is known by one or more alternative titles or names in addition to its primary title.
-
C.
hasAlternateTitleRegion
Indicates that an entity has an alternate title that is specifically used or valid within a particular geographic region.
-
D.
hasAlternativeEditionTitle
Indicates that an entity has a different or variant title used in another edition of the same work.
-
E.
alternateInterpretationOfTitle
Indicates that one title is an alternative interpretation or reading of another title, reflecting a different way the original title can be understood.
- 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_69f3491df9288190afc0b23b1d6e72ce |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fcf36d2894819089b7db8e91b63c9d |
completed | May 7, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69fcf25c0a108190bfa823474098640b |
completed | May 7, 2026, 8:13 p.m. |
Created at: May 1, 2026, 12:56 a.m.