Triple
T10804541
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alt Penedès |
E254928
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Anoia |
E250810
|
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: Anoia | Statement: [Alt Penedès, borders, Anoia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anoia Context triple: [Alt Penedès, borders, Anoia]
-
A.
Anoia
chosen
Anoia is a comarca (county) in central Catalonia, Spain, known for its mix of industrial towns and rural landscapes, with Igualada as its capital.
-
B.
Gironella
Gironella is a small municipality in Catalonia, Spain, known for its historic textile industry and location along the Llobregat River.
-
C.
Valdemaqueda
Valdemaqueda is a small municipality in the Community of Madrid, Spain, known for its rural landscape and proximity to the Sierra de Guadarrama.
-
D.
Valença
Valença is a historic fortified city in northern Portugal, situated on the Minho River near the Spanish border and known for its well-preserved medieval walls and cross-border commerce.
-
E.
Valença
Valença is a historic municipality in the state of Rio de Janeiro, Brazil, known for its colonial heritage and role in the coffee-producing region of the Sul Fluminense.
- 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_69d6aa61c15c8190a1839550c56e75e1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d73370e7388190885b104fc883456e |
completed | April 9, 2026, 5:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de567a7ea0819088a2fa10f8367d89 |
completed | April 14, 2026, 3 p.m. |
Created at: April 8, 2026, 9:18 p.m.