Triple
T15608804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harold Crick |
E375231
|
entity |
| Predicate | hasNarrativeDeviceApplied |
P23847
|
FINISHED |
| Object | omniscient voice-over narration |
—
|
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: omniscient voice-over narration | Statement: [Harold Crick, hasNarrativeDeviceApplied, omniscient voice-over narration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNarrativeDeviceApplied Context triple: [Harold Crick, hasNarrativeDeviceApplied, omniscient voice-over narration]
-
A.
hasNarrativeDevice
chosen
Indicates that one entity employs, contains, or is characterized by a particular narrative device used in storytelling or discourse.
-
B.
hasNarrative
Indicates that one entity contains, presents, or is associated with a story or narrative about another entity or subject.
-
C.
hasNarrativeEvent
Indicates that one entity includes, contains, or is associated with a specific narrative event within a story or sequence of events.
-
D.
hasNarrativeOutcome
Indicates that an event, action, or narrative element leads to or results in a particular story-related consequence or resolution.
-
E.
hasNarrativeSegments
Indicates that an entity is composed of or associated with multiple distinct narrative segments or sections.
- 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_69d85ccf2794819096cda4cbcb02d478 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e8024948190a6c711f2e5c2aac4 |
completed | April 16, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69deda844af081909e658ebc9d9b403d |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:13 a.m.