Triple
T13698105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gerry (2002 film) |
E328440
|
entity |
| Predicate | hasMinimalDialogue |
P85534
|
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), hasMinimalDialogue, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMinimalDialogue Context triple: [Gerry (2002 film), hasMinimalDialogue, true]
-
A.
hasDialogueIn
Indicates that an entity participates in or contains spoken or written dialogue within a specified context, such as a scene, work, or medium.
-
B.
hasDialogueTrait
chosen
Indicates that an entity possesses a specific characteristic or quality related to dialogue or conversational behavior.
-
C.
hasDialogueSystem
Indicates that an entity includes or is equipped with a system for managing dialogue or conversational interactions.
-
D.
hasNoSpokenDialogue
Indicates that the referenced entity does not produce any spoken dialogue within the given context or work.
-
E.
hasMultilingualDialogue
Indicates that an interaction or work contains dialogue expressed in more than one language.
- 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_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. |
Created at: April 9, 2026, 9:54 p.m.