Triple
T13698120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gerry (2002 film) |
E328440
|
entity |
| Predicate | hasMinimalPlot |
P111213
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Gerry (2002 film), hasMinimalPlot, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMinimalPlot Context triple: [Gerry (2002 film), hasMinimalPlot, true]
-
A.
hasMainPlotElement
Indicates that one entity serves as a central or primary plot element within the narrative of another entity.
-
B.
hasPlot
Indicates that an entity (such as a narrative work) possesses or is associated with a specific storyline or sequence of events.
-
C.
hasDramaticStructure
Indicates that something possesses or follows a specific dramatic structure, such as an organized sequence of narrative or theatrical elements (e.g., exposition, climax, resolution).
-
D.
hasCinematicShort
Indicates that an entity is associated with or includes a cinematic short film or short-form cinematic content.
-
E.
hasDramaticElements
Indicates that something contains features or qualities characteristic of drama, such as heightened emotion, tension, or conflict.
- 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_69d8076ff62081908a7bd79889edd7a0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc878b57c819094e7ea6d1a64211f |
completed | April 12, 2026, 4:29 p.m. |
| PD | Predicate disambiguation | batch_69dbbe9059488190a8113177c83e1481 |
completed | April 12, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69dbc59ca1a88190a6abd3bd00554c93 |
completed | April 12, 2026, 4:17 p.m. |
Created at: April 9, 2026, 9:54 p.m.