Triple
T33590791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tango (por una cabeza) |
E860412
|
entity |
| Predicate | isWidelyRecognizedFor |
P52554
|
FINISHED |
| Object | frequent use in film soundtracks |
—
|
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: frequent use in film soundtracks | Statement: [Tango (por una cabeza), isWidelyRecognizedFor, frequent use in film soundtracks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isWidelyRecognizedFor Context triple: [Tango (por una cabeza), isWidelyRecognizedFor, frequent use in film soundtracks]
-
A.
isWidelyKnownAs
Indicates that an entity is commonly referred to or recognized by a particular name or label by a broad audience.
-
B.
reconocidaPor
Indicates that an entity is recognized, acknowledged, or honored by another entity.
-
C.
fameFor
chosen
Indicates that one entity is widely known or recognized specifically because of, or in connection with, another entity.
-
D.
oftenRecognizedBy
Indicates that one entity is frequently identified, acknowledged, or noticed by another entity.
-
E.
madeInternationallyFamousBy
Indicates that one entity became widely known across multiple countries as a result of the actions, influence, or association of 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_69f3497e70e48190951c94d072879bec |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6f79a2c548190b4e8b776afc1a43a |
completed | May 3, 2026, 7:22 a.m. |
| PD | Predicate disambiguation | batch_69f6f6632dfc8190af85e258c8519207 |
completed | May 3, 2026, 7:16 a.m. |
Created at: May 1, 2026, 1:40 a.m.