Triple
T1241441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biobío River |
E26665
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Talcahuano |
E74676
|
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: Talcahuano | Statement: [Biobío River, near, Talcahuano]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Talcahuano Context triple: [Biobío River, near, Talcahuano]
-
A.
Talcahuano
chosen
Talcahuano is a major Chilean port city and naval base known for its shipyards and fishing industry.
-
B.
Rancagua
Rancagua is a major Chilean city known for its mining industry and historical significance in the country’s independence, serving as an important commercial and administrative center south of Santiago.
-
C.
Talca
Talca is a major city in central Chile known as an administrative, commercial, and agricultural hub in the Maule Valley.
-
D.
Cauquenes
Cauquenes is a provincial capital and wine-producing city in central Chile known for its agricultural economy and seismic history.
-
E.
Los Lagos
Los Lagos is a small Chilean city located in the Los Ríos Region, known for its riverside setting and role as a local agricultural and forestry center.
- 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_69a4948689d08190b3a4a3f388c02148 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bf44ac3c8190a28a333b320305fd |
completed | March 1, 2026, 10:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad4005cd4c81909cff0ed6529d1695 |
completed | March 8, 2026, 9:23 a.m. |
Created at: March 1, 2026, 7:47 p.m.