Triple
T9299660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guarda District |
E223725
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object | Trancoso |
E374160
|
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: Trancoso | Statement: [Guarda District, containsTown, Trancoso]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trancoso Context triple: [Guarda District, containsTown, Trancoso]
-
A.
Trancoso
chosen
Trancoso is a historic Portuguese town in the Centro Region, known for its medieval walls, castle, and well-preserved old quarter.
-
B.
Rocha
Rocha is a Portuguese-origin surname common in Lusophone countries and among their diasporas.
-
C.
Rocha
Rocha is a coastal department in southeastern Uruguay known for its beaches, lagoons, and ecotourism.
-
D.
Congonhas
Congonhas is a district in the city of São Paulo, Brazil, best known for giving its name to one of the country’s busiest domestic airports.
-
E.
Cardoso
Cardoso is a common Portuguese-language surname borne by numerous individuals, including prominent Brazilian political and cultural figures.
- 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_69ca8423edb08190bc0c91287a484768 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd08d070c881908bed41aada6f85ae |
completed | April 1, 2026, noon |
| NED1 | Entity disambiguation (via context triple) | batch_69d0e3924df4819095490983615b2aae |
completed | April 4, 2026, 10:10 a.m. |
Created at: March 30, 2026, 7:36 p.m.