Triple
T3085252
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guayaquil–Durán bridge |
E64355
|
entity |
| Predicate | connects |
P390
|
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: [Guayaquil–Durán bridge, connects, Durán]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Durán Context triple: [Guayaquil–Durán bridge, connects, 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.
Rivas
Rivas is a city in southwestern Nicaragua known as a regional commercial center and gateway between Lake Nicaragua and the Pacific coast.
-
C.
Carballal
Carballal is a Spanish surname, likely of Galician origin, that serves as a variant of the more common surname Carvajal.
-
D.
Belén
Belén is a town in northwestern Argentina known for its traditional weaving and role as a regional center in Catamarca Province.
-
E.
Vélez
Vélez is a Spanish-language surname common in Latin America and Spain, borne by various notable figures in arts, sports, and public life.
- 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_69ad857bb4c88190a4cf27893fcabed8 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada1eac5548190bee60ea8262c65a8 |
completed | March 8, 2026, 4:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1f89e6f5c8190993794e2c9977ee6 |
completed | March 11, 2026, 11:19 p.m. |
Created at: March 8, 2026, 3:03 p.m.