Triple
T21557615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koura |
E531933
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object | Barsa |
—
|
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: Barsa | Statement: [Koura, hasTown, Barsa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barsa Context triple: [Koura, hasTown, Barsa]
-
A.
Barsa
chosen
Barsa is a town located in the Koura District of northern Lebanon.
-
B.
Barakaldo
Barakaldo is a major industrial and residential city in the Basque Country in northern Spain, located near Bilbao along the Nervión River.
-
C.
Eibar
Eibar is an industrial town in the Basque Country of northern Spain, known historically for its arms manufacturing and its football club SD Eibar.
-
D.
Bilbao
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.
-
E.
Bilbao
Bilbao is a station on Madrid's Metro network, serving Line 1 and located in the central Chamberí district.
- 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_69e0c460232c81908de2c3819d17c00e |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eed2e14af88190bc70b4d0f3453aac |
completed | April 27, 2026, 3:07 a.m. |
Created at: April 16, 2026, 6:29 p.m.