Triple
T17018144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lola |
E412873
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object | Tango-Film |
E1029341
|
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: Tango-Film | Statement: [Lola, productionCompany, Tango-Film]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tango-Film Context triple: [Lola, productionCompany, Tango-Film]
-
A.
Tango-Film
chosen
Tango-Film is a German film distribution company known for handling releases of notable arthouse and classic films.
-
B.
TANGO
TANGO is a family of modern light rail and tram vehicles produced by the Swiss rolling stock manufacturer Stadler Rail.
-
C.
tango
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.
-
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.
Tango (por una cabeza)
"Tango (por una cabeza)" is a famous Argentine tango song composed by Carlos Gardel with lyrics by Alfredo Le Pera, widely recognized for its passionate melody and frequent use in film soundtracks.
- 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_69d886cc4170819093deddc7b8b4b6a7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d480a58c8190a3912d26debb4311 |
completed | April 18, 2026, 6:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a011b4d6cb881909b64b4368fd97fa9 |
completed | May 10, 2026, 11:57 p.m. |
Created at: April 10, 2026, 5:33 a.m.