Triple
T21811765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fados |
E538490
|
entity |
| Predicate | follows |
P134
|
FINISHED |
| Object | Tango |
—
|
NE NERFINISHED |
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: Tango | Statement: [Fados, follows, Tango]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tango Context triple: [Fados, follows, Tango]
-
A.
TANGO
TANGO is a family of modern light rail and tram vehicles produced by the Swiss rolling stock manufacturer Stadler Rail.
-
B.
tango
chosen
Tango is a passionate and dramatic partner dance and musical style that originated in the working-class neighborhoods of Buenos Aires and Montevideo in the late 19th century.
-
C.
Tango Atlantico
Tango Atlantico is a track by the German electronic music project Big World, known for its dance-oriented, melodic club sound.
-
D.
Calera de Tango
Calera de Tango is a semi-rural commune and town in central Chile known for its agricultural activity and proximity to Santiago.
-
E.
Cha-Cha
Cha-Cha is the nickname of Hall of Fame Puerto Rican first baseman Orlando Cepeda, a star slugger primarily known for his years with the San Francisco Giants in Major League Baseball.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c473f0f8819086c9d1b4a143bd67 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f07cc6cdf88190a31129acdc3bcec8 |
completed | April 28, 2026, 9:24 a.m. |
Created at: April 16, 2026, 6:53 p.m.