Triple
T21378271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A4 motorway |
E527270
|
entity |
| Predicate | improvesAccessTo |
P27318
|
FINISHED |
| Object | Bragança |
—
|
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: Bragança | Statement: [A4 motorway, improvesAccessTo, Bragança]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bragança Context triple: [A4 motorway, improvesAccessTo, Bragança]
-
A.
Bragança
chosen
Bragança is a historic city in northeastern Portugal known for its well-preserved medieval castle and role as the former seat of the House of Braganza.
-
B.
Vila Real
Vila Real is a historic city in northern Portugal known for its scenic Douro Valley surroundings and notable Baroque architecture.
-
C.
Sabrosa
Sabrosa is a small municipality in Portugal’s Douro region, historically notable as the birthplace of explorer Ferdinand Magellan.
-
D.
Alenquer
Alenquer is a historic Portuguese town and municipality in the Lisbon District, known for its wine production and scenic location along the banks of the River Alcabrichel.
-
E.
Alenquer
Alenquer is a municipality in the Brazilian state of Pará, located in the Lower Amazon region and known for its Amazonian riverside landscapes and biodiversity.
- 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_69e0b51f363c8190944000ab5523b02b |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8b0ca5e1c81909b06958459c553dc |
completed | April 22, 2026, 11:28 a.m. |
Created at: April 16, 2026, 5:11 p.m.