Triple
T12771667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linha da Beira Baixa |
E305260
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Covilhã |
E337094
|
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: Covilhã | Statement: [Linha da Beira Baixa, passesThrough, Covilhã]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Covilhã Context triple: [Linha da Beira Baixa, passesThrough, Covilhã]
-
A.
Covilhã
chosen
Covilhã is a city in central Portugal, historically known for its textile industry and as a gateway to the Serra da Estrela mountain range.
-
B.
Montemor-o-Novo
Montemor-o-Novo is a historic town and municipality in Portugal’s Alentejo region, known for its medieval castle ruins and rural landscapes.
-
C.
Lamego
Lamego is a historic city in northern Portugal known for its baroque Sanctuary of Our Lady of Remedies and its location in the Douro wine region.
-
D.
Lourinhã
Lourinhã is a coastal municipality in western Portugal known for its rich dinosaur fossil discoveries and scenic Atlantic beaches.
-
E.
Sernancelhe
Sernancelhe is a municipality in northern Portugal known for its historic granite architecture, religious heritage, and scenic rural landscapes.
- 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_69d7bdf2b43c819098ae5aa68e61ea58 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96df5b68481908a5d40516b09be52 |
completed | April 10, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75d7a9e6c81908ae78daace02e7ec |
completed | May 3, 2026, 2:36 p.m. |
Created at: April 9, 2026, 5:28 p.m.