Triple
T35142766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sticky Shoes |
E1014739
|
entity |
| Predicate | isFictionalWorkWithin |
P176587
|
FINISHED |
| Object | diegetic music in Friends |
—
|
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: diegetic music in Friends | Statement: [Sticky Shoes, isFictionalWorkWithin, diegetic music in Friends]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isFictionalWorkWithin Context triple: [Sticky Shoes, isFictionalWorkWithin, diegetic music in Friends]
-
A.
isForFictionalWork
chosen
Indicates that something is intended to be used in, associated with, or specifically created for a fictional work.
-
B.
hasFictionalWork
Indicates that one entity is the creator, owner, or source of a fictional work associated with another entity.
-
C.
worksInFictionalContext
Indicates that an entity performs work or fulfills a role within a fictional or imagined setting rather than in real-world circumstances.
-
D.
isSetInFictionalUniverse
Indicates that a narrative work takes place within a specific fictional universe or setting.
-
E.
worksWithInFiction
Indicates that two fictional characters are depicted as collaborating, interacting, or being associated with each other within a narrative work.
- 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_69f76dda7c108190a2ffd93eb6c341a7 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78cab90cc8190827145ac515d203b |
completed | May 3, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69f78b9106008190930b3b3675b737d6 |
completed | May 3, 2026, 5:53 p.m. |
Created at: May 3, 2026, 4:02 p.m.