Triple
T11123209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amazonía Ecuatoriana |
E263068
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Tena |
E386364
|
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: Tena | Statement: [Amazonía Ecuatoriana, hasMajorCity, Tena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tena Context triple: [Amazonía Ecuatoriana, hasMajorCity, Tena]
-
A.
Tena
chosen
Tena is a small city in Ecuador’s Amazon region known as a gateway for jungle tourism and whitewater rafting.
-
B.
Tena
Tena is a municipality in the Tequendama Province of the Cundinamarca Department in central Colombia, known for its rural landscapes and proximity to Bogotá.
-
C.
Teià
Teià is a small coastal municipality in Catalonia, Spain, situated in the Maresme comarca near Barcelona.
-
D.
Yato
Yato is a small village on Pukapuka Atoll in the Cook Islands, known for its traditional Polynesian community and remote Pacific island setting.
-
E.
Uma
Uma is an Austronesian language spoken primarily in Central Sulawesi, Indonesia.
- 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_69d6aa9b46cc8190b19f9f0cc45bf322 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7e82e933481908550499cf9dd6531 |
completed | April 9, 2026, 5:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e42d8643748190a7801fc401dd2b5a |
completed | April 19, 2026, 1:19 a.m. |
Created at: April 8, 2026, 9:28 p.m.