Triple
T20782476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dwight’s Used Records |
E511524
|
entity |
| Predicate | hasTrackCollectionType |
P338
|
FINISHED |
| Object | alternative rock tracks |
—
|
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: alternative rock tracks | Statement: [Dwight’s Used Records, hasTrackCollectionType, alternative rock tracks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrackCollectionType Context triple: [Dwight’s Used Records, hasTrackCollectionType, alternative rock tracks]
-
A.
hasTrack
Indicates that one entity possesses, includes, or is associated with a specific track (such as a path, course, or recorded item).
-
B.
hasCollectionType
chosen
Indicates that an entity is associated with or organized under a specific type or category of collection.
-
C.
hasTrackSection
Indicates that an entity includes, is composed of, or is associated with a specific section or segment of a track.
-
D.
hasTrackContext
Indicates that an entity is associated with or occurs within a particular track-related context (such as a specific track, route, or sequence).
-
E.
hasCollection
Indicates that an entity possesses, maintains, or is associated with a set or group of related items treated as a collection.
- 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_69e0b4cac7a48190a715cb3d545df2b4 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c28870e481909e7cbcdd6d4bc247 |
completed | April 21, 2026, 12:19 a.m. |
| PD | Predicate disambiguation | batch_69e5c0550ec481908a0877fb2409d983 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 12:38 p.m.