Triple
T21589255
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cruz Alta |
E532735
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Sintra town |
—
|
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: Sintra town | Statement: [Cruz Alta, near, Sintra town]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sintra town Context triple: [Cruz Alta, near, Sintra town]
-
A.
Sintra
chosen
Sintra is a historic Portuguese town near Lisbon, renowned for its romantic 19th-century palaces, castles, and lush hillside landscapes.
-
B.
Centro Histórico de Sintra
Centro Histórico de Sintra is the historic center of Sintra, Portugal, renowned for its romantic architecture, palaces, and UNESCO World Heritage status.
-
C.
Nova Sintra
Nova Sintra is the main town and administrative center of the island of Brava in Cape Verde, known for its colonial architecture and mountainous setting.
-
D.
Vila do Conde
Vila do Conde is a coastal city in northern Portugal known for its historic shipbuilding heritage, beaches, and well-preserved medieval architecture.
-
E.
Alcobaça
Alcobaça is a historic Portuguese city best known for its UNESCO-listed Cistercian monastery, one of the country’s most important medieval monuments.
- 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_69e0c46251648190876f0427cf2d321b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eefadb25108190b7a3d2e8dfc8ae60 |
completed | April 27, 2026, 5:57 a.m. |
Created at: April 16, 2026, 6:32 p.m.