Triple
T3776419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Highlights |
E83317
|
entity |
| Predicate | usesVocalEffect |
P9331
|
FINISHED |
| Object | Auto-Tune |
E294869
|
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: Auto-Tune | Statement: [Highlights, usesVocalEffect, Auto-Tune]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Auto-Tune Context triple: [Highlights, usesVocalEffect, Auto-Tune]
-
A.
Auto-Tune
chosen
Auto-Tune is an audio processing technology that automatically corrects or stylizes vocal pitch, widely used in music production for both subtle tuning and distinctive robotic effects.
-
B.
Harmonizer
Harmonizer is a 2021 studio album by American garage rock musician Ty Segall, noted for its heavier, synth-laced sound and experimental production.
-
C.
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.
-
D.
DAW
DAW was a United Nations division focused on promoting gender equality and advancing the status and rights of women worldwide.
-
E.
Versoix
Versoix is a Swiss municipality on the shores of Lake Geneva, known as a residential suburb of Geneva with lakeside promenades and a mix of urban and natural landscapes.
- 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_69ad8b235e608190b5a2b1d1bfcef50b |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcc5be3c48190a72e840d8214bb74 |
completed | March 8, 2026, 7:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4e534a02c8190b8dd76ed965f393f |
completed | March 14, 2026, 4:33 a.m. |
Created at: March 8, 2026, 3:36 p.m.