Triple
T8848451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schorndorf |
E210568
|
entity |
| Predicate | twinnedWith |
P1072
|
FINISHED |
| Object | Errenteria |
E384743
|
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: Errenteria | Statement: [Schorndorf, twinnedWith, Errenteria]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Errenteria Context triple: [Schorndorf, twinnedWith, Errenteria]
-
A.
Errenteria
chosen
Errenteria is a town and municipality in the province of Gipuzkoa in Spain’s Basque Country, known for its industrial heritage and proximity to San Sebastián.
-
B.
Hondarribia
Hondarribia is a historic coastal town in Spain’s Basque Country, known for its well-preserved old quarter, fishing port, and location on the border with France.
-
C.
Urrutikoetxea
Urrutikoetxea is the Basque surname of Spanish actress and singer Najwa Nimri, reflecting her Basque heritage.
-
D.
Sestao
Sestao is an industrial town and municipality in the Basque province of Biscay in northern Spain, situated along the Nervión River near Bilbao.
-
E.
Zarautz
Zarautz is a coastal town in Spain’s Basque Country, known for its long sandy beach and strong surfing culture.
- 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_69ca838967bc8190b46c3c80a2887ea4 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc60aa6db0819097c3257499200afc |
completed | April 1, 2026, 12:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf89c6788881908d6f5c49434b556d |
completed | April 3, 2026, 9:35 a.m. |
Created at: March 30, 2026, 6:49 p.m.