Triple
T1786430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wrap Me Up in Your Love |
E39402
|
entity |
| Predicate | featuresHolidayImagery |
P17123
|
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: [Wrap Me Up in Your Love, featuresHolidayImagery, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresHolidayImagery Context triple: [Wrap Me Up in Your Love, featuresHolidayImagery, true]
-
A.
usesImageryOf
chosen
Indicates that one entity employs or incorporates visual or sensory imagery that depicts, references, or symbolically represents another entity.
-
B.
featureOfInterest
Indicates the entity or object that is the primary subject or focus of the described observation, measurement, or analysis.
-
C.
relatedHoliday
Indicates that there is an association or connection between two holidays, such as thematic, temporal, cultural, or contextual relatedness.
-
D.
oftenPhotographedAt
Indicates that an entity is frequently the subject of photographs taken at a particular location or during a specific event.
-
E.
photographedByTourists
Indicates that the subject has been photographed by people visiting as tourists.
- 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_69a88631854081909723959921e45c2b |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab75457e54819096b8c6ae8c65550c |
completed | March 7, 2026, 12:45 a.m. |
| PD | Predicate disambiguation | batch_69aa61d165688190924962a98e07ff69 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:32 p.m.