Triple
T10206927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucy Does a TV Commercial |
E242220
|
entity |
| Predicate | featuresWorkOfFiction |
P31994
|
FINISHED |
| Object | fictional health tonic |
—
|
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: fictional health tonic | Statement: [Lucy Does a TV Commercial, featuresWorkOfFiction, fictional health tonic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresWorkOfFiction Context triple: [Lucy Does a TV Commercial, featuresWorkOfFiction, fictional health tonic]
-
A.
workInFiction
Indicates that one entity is a fictional work in which the other entity appears or is set.
-
B.
literaryFeature
Indicates a relationship where something possesses or exhibits a characteristic, device, or stylistic element used in literature.
-
C.
hasFictionComponent
chosen
Indicates that something includes, contains, or is composed in part of a fictional element or work.
-
D.
literaryWorkInStory
Indicates that one literary work is referenced, featured, or embedded within the narrative of another story.
-
E.
fictionalMedium
Indicates that a work of fiction is presented or conveyed through a particular medium or format (such as a book, film, game, or comic).
- 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa22071c819095febd18dd607978 |
completed | April 6, 2026, 12:42 p.m. |
| PD | Predicate disambiguation | batch_69d39559e5ac8190b88eca75956b7e6a |
completed | April 6, 2026, 11:13 a.m. |
Created at: April 6, 2026, 10:55 a.m.