Triple
T27783615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gump and Co. |
E699399
|
entity |
| Predicate | hasSequelRelationToFilm |
P1961
|
FINISHED |
| Object | Forrest Gump (1994 film) |
E35378
|
NE 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: Forrest Gump (1994 film) | Statement: [Gump and Co., hasSequelRelationToFilm, Forrest Gump (1994 film)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSequelRelationToFilm Context triple: [Gump and Co., hasSequelRelationToFilm, Forrest Gump (1994 film)]
-
A.
hasSequelOrRelated
Indicates that one work follows, continues, or is otherwise narratively or thematically related to another work.
-
B.
hasSequelDepiction
Indicates that one depiction of something is followed by another depiction that continues its story or sequence.
-
C.
hasSequel
chosen
Indicates that one work is followed by another work that continues its story, timeline, or thematic development.
-
D.
hasSequelAdaptation
Indicates that an original work has a subsequent adaptation that continues its story or follows it in sequence.
-
E.
hasSequelType
Indicates that one work has a sequel of a specified type or category in relation to another work.
- F. None of above.
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_69ef6a4b5a9081909c9111396c2be3d2 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69fd0d0ba5c48190bddb3f0e6637544c |
completed | May 7, 2026, 10:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a15b877f1a48190942ea16156de7e28 |
completed | May 26, 2026, 3:12 p.m. |
| PD | Predicate disambiguation | batch_69fd0c4324a8819086c90adf46216e0e |
completed | May 7, 2026, 10:03 p.m. |
Created at: April 27, 2026, 5:11 p.m.