Triple
T33209887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marlee |
E850122
|
entity |
| Predicate | inFilmAdaptationName |
P131519
|
FINISHED |
| Object | Marlee |
—
|
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: Marlee | Statement: [Marlee, inFilmAdaptationName, Marlee]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inFilmAdaptationName Context triple: [Marlee, inFilmAdaptationName, Marlee]
-
A.
inFilmAdaptation
Indicates that one work or element appears within, or is incorporated into, a film adaptation of another work.
-
B.
hasFilmAdaptationTitle
chosen
Indicates that a creative work has a film adaptation whose title is given by the related value.
-
C.
titleOfBookAdaptation
Indicates that one entity is the title of a book from which the other entity (an adaptation, such as a film or series) is derived.
-
D.
filmAdaptationOfWork
Indicates that a film is an adaptation based on the narrative content of a specific original work.
-
E.
filmAdaptationStarred
Indicates that a particular person played a starring role in a specific film adaptation of a work.
- 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_69f3495fb92c819083ce65d0ddee7a76 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6dd3cc0648190a275812d6711275a |
completed | May 3, 2026, 5:29 a.m. |
| PD | Predicate disambiguation | batch_69f6d82eaee081908f06a71546315aea |
completed | May 3, 2026, 5:07 a.m. |
Created at: May 1, 2026, 1:30 a.m.