Triple
T33349648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big Momma's House 2 (film score) |
E853897
|
entity |
| Predicate | scoredScenes |
P176821
|
FINISHED |
| Object | comedy sequences |
—
|
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: comedy sequences | Statement: [Big Momma's House 2 (film score), scoredScenes, comedy sequences]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scoredScenes Context triple: [Big Momma's House 2 (film score), scoredScenes, comedy sequences]
-
A.
numberOfScenes
Indicates the total count of distinct scenes associated with or contained within an entity.
-
B.
scoredAsPartOf
Indicates that an entity achieved a score or rating specifically within the context of being part of a larger group, event, or composite activity.
-
C.
scoringRecord
Indicates that there exists a record documenting a scoring event or outcome associated with the given entities.
-
D.
scenes
Indicates that one entity is a scene or setting in which the other entity occurs, appears, or is depicted.
-
E.
coScoredWith
Indicates that two or more entities received the same score or were evaluated with an identical scoring outcome in a shared context.
- 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_69f3496a1a588190bad9cbe9221144e0 |
completed | April 30, 2026, 12:22 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. |
| PDg | Predicate description generation | batch_69f6f37f36ac8190b1bff8711d6771cb |
completed | May 3, 2026, 7:04 a.m. |
Created at: May 1, 2026, 1:34 a.m.