Triple
T7844976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Betania Dam |
E181900
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object | Neiva |
E174528
|
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: Neiva | Statement: [Betania Dam, nearbyCity, Neiva]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Neiva Context triple: [Betania Dam, nearbyCity, Neiva]
-
A.
Neiva
chosen
Neiva is a major city in southwestern Colombia known as the economic and cultural center of the upper Magdalena River valley.
-
B.
Bemposta
Bemposta is a civil parish located within the municipality of Abrantes in central Portugal.
-
C.
Barretos
Barretos is a municipality in the Brazilian state of São Paulo, widely known for hosting one of the largest annual rodeo festivals in Latin America.
-
D.
Arruda
Arruda is a neighborhood in Recife, Brazil, best known for housing the Estádio do Arruda, home stadium of the Santa Cruz Futebol Clube.
-
E.
Neive
Neive is a picturesque medieval village in Italy’s Piedmont wine region, renowned for its historic charm and production of Barbaresco and other Langhe wines.
- 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_69ca8285d6488190a95d4c02d7354b53 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb163d92fc8190a4efcb08d6b3d404 |
completed | March 31, 2026, 12:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc55fe5b4c8190b35ddbef8c372269 |
completed | March 31, 2026, 11:17 p.m. |
Created at: March 30, 2026, 4:48 p.m.