Triple
T15568487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alenquer |
E374177
|
entity |
| Predicate | hasSubregion |
P285
|
FINISHED |
| Object | Oeste |
E1067787
|
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: Oeste | Statement: [Alenquer, hasSubregion, Oeste]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oeste Context triple: [Alenquer, hasSubregion, Oeste]
-
A.
Oeste
chosen
Oeste is a coastal subregion of central Portugal known for its Atlantic beaches, agricultural production, and historic towns.
-
B.
Suroeste
Suroeste is a district of Santa Cruz de Tenerife known for its largely residential character and mix of urban and semi-rural areas on the island of Tenerife in Spain’s Canary Islands.
-
C.
Юго-Западная
Юго-Западная is a Moscow Metro station on the Sokolnicheskaya Line, serving the southwestern part of the city.
-
D.
Northwest
Northwest is a public university in Maryville, Missouri, known for its comprehensive undergraduate and graduate programs and strong emphasis on applied learning.
-
E.
Nordeste
Nordeste is a picturesque municipality on the northeastern tip of São Miguel Island in the Azores, known for its dramatic coastal cliffs, lush landscapes, and scenic viewpoints.
- 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_69d85ccd575081908909b71a3f3e3a61 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04dde90b081908284d9258d4462e3 |
completed | April 16, 2026, 2:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff4c4440a481909699a7eee25a4b24 |
completed | May 9, 2026, 3:01 p.m. |
Created at: April 10, 2026, 4:10 a.m.