Triple
T4063053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vila Nova de Cacela |
E86259
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Altura |
E225798
|
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: Altura | Statement: [Vila Nova de Cacela, hasPart, Altura]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Altura Context triple: [Vila Nova de Cacela, hasPart, Altura]
-
A.
Altura
chosen
Altura is a coastal civil parish in Portugal’s Algarve region, known for its long sandy beaches and tourism.
-
B.
Alta
Alta is a small mountain town in Utah best known for its world-class powder skiing at Alta Ski Area in the Wasatch Range.
-
C.
Alta
Alta is a town in northern Norway known for its Arctic location, winter sports, and proximity to the Northern Lights.
-
D.
Tepehuán
The Tepehuán are an Indigenous people of northern Mexico known for their distinct language, traditional agriculture, and cultural practices rooted in the rugged highlands of the Sierra Madre Occidental.
-
E.
Hoche
Hoche is a Paris Métro station located in the northeastern suburb of Pantin, serving as a stop on the city’s Line 5.
- 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_69aed93c69208190a4efac0efe3cd69b |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefbd60cc081908764fcc8206bc1ef |
completed | March 9, 2026, 4:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b562ae949c819092affaaca97c16d1 |
completed | March 14, 2026, 1:29 p.m. |
Created at: March 9, 2026, 3:38 p.m.