Triple
T14540698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zaba |
E341160
|
entity |
| Predicate | recordLabel |
P1500
|
FINISHED |
| Object | Wolf Tone |
E341163
|
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: Wolf Tone | Statement: [Zaba, recordLabel, Wolf Tone]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wolf Tone Context triple: [Zaba, recordLabel, Wolf Tone]
-
A.
Wolf Tone
chosen
Wolf Tone is a British independent record label known for signing innovative alternative and electronic artists such as Glass Animals.
-
B.
Audion
Audion is an early triode vacuum tube invented by Lee de Forest that enabled the amplification of electrical signals and was crucial to the development of radio and electronics.
-
C.
Zeppotron
Zeppotron is a British television production company best known for co-producing the acclaimed anthology series "Black Mirror."
-
D.
Touchstone
Touchstone is the witty and sharp-tongued court jester in Shakespeare’s comedy "As You Like It," known for his clever wordplay and satirical commentary.
-
E.
Touchstone
Touchstone is a publishing imprint known for releasing a wide range of commercial fiction and nonfiction titles.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d822db9c8481908213ceb39585f792 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb1bd0dd4819094c8b2f2aa6b1c5e |
completed | April 14, 2026, 9:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdfb76fb58819088e5a0101143a401 |
completed | May 8, 2026, 3:04 p.m. |
Created at: April 10, 2026, 1:22 a.m.