Triple
T3531831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Talcahuano |
E74676
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Concepción |
E15421
|
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: Concepción | Statement: [Talcahuano, locatedNear, Concepción]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Concepción Context triple: [Talcahuano, locatedNear, Concepción]
-
A.
Concepción
chosen
Concepción is a major Chilean city in the south-central part of the country, known as an important industrial, commercial, and educational center.
-
B.
Concepción
Concepción is an active stratovolcano located on Ometepe Island in Lake Nicaragua, known for its symmetrical cone shape and frequent eruptions.
-
C.
Concepción
Concepción was one of the ships in Ferdinand Magellan’s expedition that took part in the first circumnavigation of the globe.
-
D.
Concepción
Concepción is a city in northern Paraguay known as a regional commercial and river port hub.
-
E.
La Serena
La Serena is a coastal city in northern Chile known for its colonial architecture, beaches, and role as a gateway to major astronomical observatories in the region.
- 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_69ad85d1a3948190931fd1ea1f49717b |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc9a14c881908932b17ed3eececb |
completed | March 8, 2026, 6:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b51203d6148190a9946a3f274e21a5 |
completed | March 14, 2026, 7:45 a.m. |
Created at: March 8, 2026, 3:19 p.m.