Triple
T23009381
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Split-Rocker |
E572864
|
entity |
| Predicate | exhibitedAt |
P149
|
FINISHED |
| Object | Bilbao |
—
|
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: Bilbao | Statement: [Split-Rocker, exhibitedAt, Bilbao]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bilbao Context triple: [Split-Rocker, exhibitedAt, Bilbao]
-
A.
Bilbao
Bilbao is a station on Madrid's Metro network, serving Line 1 and located in the central Chamberí district.
-
B.
Bilbao
chosen
Bilbao is a major port city in northern Spain renowned for its industrial heritage, cultural institutions like the Guggenheim Museum, and role as an economic hub of the Basque Country.
-
C.
Galdakao
Galdakao is a municipality in the province of Biscay in Spain’s Basque Country, located near Bilbao in the Greater Bilbao metropolitan area.
-
D.
Bilbao metropolitan area
The Bilbao metropolitan area is a major urban and industrial region in northern Spain centered on the city of Bilbao, known for its economic importance, cultural institutions, and role as the core of Greater Bilbao in the Basque Country.
-
E.
Donostia-San Sebastián
Donostia-San Sebastián is a coastal city in Spain’s Basque Country renowned for its picturesque bay, beaches, and world-class gastronomy.
- 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_69e245b764cc8190a51be76f1d9611e1 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1835919b08190ba78e182b87358d4 |
completed | April 29, 2026, 4:04 a.m. |
Created at: April 17, 2026, 3:51 p.m.