Triple
T19419603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cerbère |
E485813
|
entity |
| Predicate | borderWith |
P224
|
FINISHED |
| Object | Portbou |
E170470
|
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: Portbou | Statement: [Cerbère, borderWith, Portbou]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Portbou Context triple: [Cerbère, borderWith, Portbou]
-
A.
Portbou
chosen
Portbou is a small coastal town in northeastern Catalonia, Spain, near the French border, known as the place where philosopher Walter Benjamin died while fleeing Nazi-occupied Europe.
-
B.
Cadaqués
Cadaqués is a picturesque coastal town on Spain’s Costa Brava, renowned for its whitewashed houses, rocky coves, and association with artist Salvador Dalí.
-
C.
Blanes
Blanes is a coastal town in Catalonia, Spain, known as the southern gateway to the Costa Brava and popular for its beaches, botanical gardens, and summer tourism.
-
D.
Arenys de Mar
Arenys de Mar is a coastal town and municipality in the Maresme comarca of Catalonia, Spain, known for its fishing port and Mediterranean beaches.
-
E.
Lloret de Mar
Lloret de Mar is a popular Mediterranean coastal resort town on Spain’s Costa Brava, known for its beaches, nightlife, and tourism.
- 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_69d8e8d688f881909c85104a62e09d8a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63213b6ec8190b89982b554a0f6e7 |
completed | April 20, 2026, 2:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0733d00204819099957699ba6ceb76 |
completed | May 15, 2026, 2:55 p.m. |
Created at: April 10, 2026, 1:37 p.m.