Triple
T36483560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alouette |
E898878
|
entity |
| Predicate | hasTuneUsedFor |
P149801
|
FINISHED |
| Object | parodies |
—
|
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: parodies | Statement: [Alouette, hasTuneUsedFor, parodies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTuneUsedFor Context triple: [Alouette, hasTuneUsedFor, parodies]
-
A.
usesTuneOf
chosen
Indicates that one work is created to be performed with, or is based on, the melody or musical setting originally belonging to another work.
-
B.
hasTuneOrigin
Indicates that one entity’s tune or melody originates from, is derived from, or is based on another entity.
-
C.
musicUsed
Indicates that one entity makes use of or incorporates another entity as music, such as in a performance, production, or media context.
-
D.
tunedOrUntuned
Indicates whether something is in a properly adjusted or calibrated state (tuned) or not (untuned).
-
E.
trackUsed
Indicates that a particular track (such as a route, path, or media track) has been utilized or selected in a given context.
- 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_69f76e5a0e088190a2b6706aeb41723c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bccf05bc8190b61fdb2b2a315811 |
completed | May 3, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:10 p.m.