Triple
T9148685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sonora |
E219525
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Cajeme |
E172151
|
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: Cajeme | Statement: [Sonora, hasMajorCity, Cajeme]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cajeme Context triple: [Sonora, hasMajorCity, Cajeme]
-
A.
Cajeme
chosen
Cajeme is a major municipality and agricultural and industrial center in the southern part of the Mexican state of Sonora, best known for its main city Ciudad Obregón.
-
B.
Pacasmayo
Pacasmayo is a coastal city in northern Peru known for its long pier, surfing beaches, and colonial-era architecture.
-
C.
Cáqueza
Cáqueza is a small municipality and town in the Andean region of central Colombia, known for its rural landscapes and proximity to Bogotá in the department of Cundinamarca.
-
D.
Chacala
Chacala is a small coastal village and beach destination on Mexico’s Pacific coast in the state of Nayarit, known for its tranquil atmosphere, surfing, and ecotourism.
-
E.
Loiceño
Loiceño is the Spanish demonym for a person from the municipality of Loíza in Puerto Rico.
- 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_69ca83e121dc81909912bd66953081c5 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca91a1fd08190a5bb3d9280439b09 |
completed | April 1, 2026, 5:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d04833858081909b616325f0e6f787 |
completed | April 3, 2026, 11:07 p.m. |
Created at: March 30, 2026, 7:20 p.m.