Triple
T24300624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Habit (2021 film) |
E606085
|
entity |
| Predicate | hasOnlinePetition |
P155471
|
FINISHED |
| Object | calls for film to be banned |
—
|
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: calls for film to be banned | Statement: [Habit (2021 film), hasOnlinePetition, calls for film to be banned]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOnlinePetition Context triple: [Habit (2021 film), hasOnlinePetition, calls for film to be banned]
-
A.
containsPetition
Indicates that one entity includes or holds a petition within it, either as content or as a component.
-
B.
numberOfPetitions
Indicates the total count of petitions associated with a given entity or context.
-
C.
keyPetition
Indicates that an entity serves as the primary or central petition associated with another entity or context.
-
D.
hasPoliticalDemand
Indicates that an entity expresses, supports, or is associated with a specific political request, claim, or requirement directed toward authorities or governance structures.
-
E.
typeOfPetition
Indicates the specific category or kind of petition that a given petition instance belongs to.
- F. None of above. chosen
Provenance (4 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_69e29549335881909cbf27adcaba1cf0 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f2915e4ffc8190bf711dae443b3ec1 |
completed | April 29, 2026, 11:16 p.m. |
| PD | Predicate disambiguation | batch_69f1c45c6ec081908401b69424428100 |
completed | April 29, 2026, 8:42 a.m. |
| PDg | Predicate description generation | batch_69f1c6d4e99081909f61899eccafb73e |
completed | April 29, 2026, 8:52 a.m. |
Created at: April 18, 2026, 12:09 a.m.