Triple
T28701684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Play-Tone Records |
E729567
|
entity |
| Predicate | associatedFictionalSong |
P56230
|
FINISHED |
| Object | That Thing You Do! |
E62652
|
NE 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: That Thing You Do! | Statement: [Play-Tone Records, associatedFictionalSong, That Thing You Do!]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedFictionalSong Context triple: [Play-Tone Records, associatedFictionalSong, That Thing You Do!]
-
A.
hasFictionalSong
chosen
Indicates that one entity includes, features, or is associated with a song that is fictional or exists only within a narrative context.
-
B.
isFictionalSong
Indicates that the referenced song exists only in fiction (e.g., within a story, film, game, or other fictional context) and not as a real-world musical work.
-
C.
fictionalCharacterAssociatedWith
Indicates that there is a notable connection or association between a fictional character and another entity, such as a work, creator, or universe.
-
D.
featuresFictionalMusical
Indicates that a work includes or prominently involves a fictional musical as part of its content or storyline.
-
E.
lyricsAdaptedFrom
Indicates that the lyrics of one work are derived, adapted, or modified from the lyrics of another pre-existing work.
- F. None of above.
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_69f043e6e9688190b6bdd6e5665498ff |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_6a01b50490e481908eb1d675561fdde2 |
completed | May 11, 2026, 10:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a24a248e1248190aca46a5939cb0350 |
completed | June 6, 2026, 10:42 p.m. |
| PD | Predicate disambiguation | batch_6a01b44b106481908aa98a3f1eb2c119 |
completed | May 11, 2026, 10:49 a.m. |
Created at: April 28, 2026, 5:42 a.m.