Triple
T20878512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Three-Course Dinner Chewing Gum |
E514082
|
entity |
| Predicate | targetConsumerInStory |
P142218
|
FINISHED |
| Object | people who like chewing gum |
—
|
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: people who like chewing gum | Statement: [Three-Course Dinner Chewing Gum, targetConsumerInStory, people who like chewing gum]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetConsumerInStory Context triple: [Three-Course Dinner Chewing Gum, targetConsumerInStory, people who like chewing gum]
-
A.
audienceWithinStory
Indicates that an audience exists as an internal, in-story observer or listener within the narrative itself, rather than outside it.
-
B.
followsStoryOf
Indicates that one narrative, account, or storyline continues from, is based on, or is derived from the events or structure of another.
-
C.
targetConsumerNeed
Indicates that something is intended to address, satisfy, or be directed toward a specific need or requirement of a consumer.
-
D.
roleInStories
Indicates the specific function, position, or character part an entity plays within one or more stories.
-
E.
associatedWithPersonInStory
Indicates that one entity has a connection or involvement with a specific person within the context of a story.
- 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_69e0b4f733f081908a401c0b7beb0b9f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c6775f108190a79cd5e8c31cecf6 |
completed | April 21, 2026, 12:36 a.m. |
| PD | Predicate disambiguation | batch_69e5c9a8dc148190b33ff51894e2a8f9 |
completed | April 20, 2026, 6:37 a.m. |
| PDg | Predicate description generation | batch_69e5d53c4d6881909b4d0a716fa5ed4a |
completed | April 20, 2026, 7:26 a.m. |
Created at: April 16, 2026, 12:45 p.m.