Triple
T13749805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Domestic Violence Part 2 |
E330313
|
entity |
| Predicate | narrativeSequelTo |
P1961
|
FINISHED |
| Object | Domestic Violence |
—
|
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: Domestic Violence | Statement: [Domestic Violence Part 2, narrativeSequelTo, Domestic Violence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: narrativeSequelTo Context triple: [Domestic Violence Part 2, narrativeSequelTo, Domestic Violence]
-
A.
hasSequel
chosen
Indicates that one work is followed by another work that continues its story, timeline, or thematic development.
-
B.
narrativeSequence
Indicates that one event or narrative element follows another in a temporal or logical storytelling order.
-
C.
hasSequelInCanon
Indicates that a work has a subsequent work that continues its story within the officially recognized continuity.
-
D.
hasSecondSequel
Indicates that an entity has a second sequel, i.e., a third work in a series that continues its storyline or content.
-
E.
hasSequelByAnotherAuthor
Indicates that a work has a sequel created by a different author than the original.
- 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_69d81c573f288190aa2403d484fa3d49 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02148c208190a882927905a861a6 |
completed | April 14, 2026, 9 a.m. |
| PD | Predicate disambiguation | batch_69dbbe950b148190ba0df8a749269ec6 |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 10:08 p.m.