Triple
T516785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guayas River |
E10725
|
entity |
| Predicate | majorCityOnBanks |
P14915
|
FINISHED |
| Object | Durán |
E68436
|
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: Durán | Statement: [Guayas River, majorCityOnBanks, Durán]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Durán Context triple: [Guayas River, majorCityOnBanks, Durán]
-
A.
Durán
chosen
Durán is an Ecuadorian city in the Guayas Province, located across the Guayas River from Guayaquil and serving as an important transport and industrial hub.
-
B.
Belén
Belén is a town in northwestern Argentina known for its traditional weaving and role as a regional center in Catamarca Province.
-
C.
León
León is a historic city and former kingdom in northwestern Spain, renowned for its medieval architecture and significant role in the formation of the Spanish state.
-
D.
San Borja
San Borja is a primarily residential and commercial district in Lima, Peru, known for its middle- to upper-class neighborhoods, green areas, and cultural institutions.
-
E.
San Isidro
San Isidro is an upscale, modern district of Lima, Peru, known for its financial center, embassies, parks, and high-end residential areas.
- 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_69a2e84a0d08819087e01863fcd9abf1 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f3b7557c8190a29cf1de359ea2ea |
completed | Feb. 28, 2026, 1:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4e0277eb08190984ff5bcb9f349a0 |
completed | March 2, 2026, 12:56 a.m. |
Created at: Feb. 28, 2026, 1:12 p.m.