Triple
T15932865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tena |
E386364
|
entity |
| Predicate | roadAccessFrom |
P22549
|
FINISHED |
| Object | Baños |
E867541
|
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: Baños | Statement: [Tena, roadAccessFrom, Baños]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baños Context triple: [Tena, roadAccessFrom, Baños]
-
A.
Baños
chosen
Baños is a popular tourist town in central Ecuador known for its hot springs, waterfalls, and adventure sports.
-
B.
San Juan de Baños
San Juan de Baños is one of the oldest surviving churches in Spain, a 7th-century Visigothic basilica renowned for its early medieval architecture and historical significance.
-
C.
Banyo
Banyo is a town and commune in the Adamawa Region of Cameroon known as a local administrative and trading center.
-
D.
Los Baños
Los Baños is a municipality in the Philippines known as a major center for agricultural research and education, particularly in rice science.
-
E.
San Andrés Larráinzar
San Andrés Larráinzar is a highland town in Chiapas, Mexico, known as a cultural and political center for the Tzotzil Maya people.
- 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_69d86da750008190987eb26be3f6c118 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e156a6d9b88190b461d12d69b12ac0 |
completed | April 16, 2026, 9:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb5b514108190965e77346d8b476e |
completed | May 9, 2026, 10:31 p.m. |
Created at: April 10, 2026, 4:53 a.m.