Triple
T31315733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Message in a Bottle (Taylor’s Version) (From the Vault) |
E798589
|
entity |
| Predicate | hasTaylor’sVersionDesignation |
P171566
|
FINISHED |
| Object | Taylor’s Version |
—
|
NE NERFINISHED |
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: Taylor’s Version | Statement: [Message in a Bottle (Taylor’s Version) (From the Vault), hasTaylor’sVersionDesignation, Taylor’s Version]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTaylor’sVersionDesignation Context triple: [Message in a Bottle (Taylor’s Version) (From the Vault), hasTaylor’sVersionDesignation, Taylor’s Version]
-
A.
isTaylor’sVersion
chosen
Indicates that a musical work is the re-recorded “Taylor’s Version” of an original release by Taylor Swift.
-
B.
typicalDesignation
Indicates that one entity is the usual or commonly used designation (name, label, or title) for another entity.
-
C.
hasTarn
Indicates that something possesses or contains a tarn, i.e., a small mountain lake or pool.
-
D.
hasDifferentDesignsFor
Indicates that one entity provides or uses multiple distinct designs tailored for different other entities or contexts.
-
E.
Typer
Indicates that one entity serves as the type or classification for another entity.
- 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_69f224e1932c81908fef14f7b03a10b7 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6cd126fcc8190aa1f1f146e45ec0c |
completed | May 3, 2026, 4:20 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1470808190b70cdfd7a6395670 |
completed | May 3, 2026, 4:16 a.m. |
Created at: April 29, 2026, 9:15 p.m.