Triple
T11869284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Martín Region |
E282364
|
entity |
| Predicate | largestCity |
P235
|
FINISHED |
| Object | Tarapoto |
E295056
|
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: Tarapoto | Statement: [San Martín Region, largestCity, Tarapoto]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tarapoto Context triple: [San Martín Region, largestCity, Tarapoto]
-
A.
Tarapoto
chosen
Tarapoto is a city in northern Peru known as a gateway to the Amazon rainforest and a regional hub for tourism and commerce.
-
B.
Tucupita
Tucupita is a small Venezuelan city that serves as the capital of Delta Amacuro state and the main urban center near the Orinoco Delta.
-
C.
Arauquita
Arauquita is a Colombian municipality in the eastern plains region, known for its agricultural activities and proximity to the Venezuelan border.
-
D.
Puerto Maldonado
Puerto Maldonado is a frontier city in the Peruvian Amazon known as a gateway to the Madre de Dios rainforest and nearby biodiversity-rich reserves.
-
E.
Camaná
Camaná is a coastal city in southern Peru known for its beaches, agriculture, and role as a regional commercial 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_69d6ab2945d081908a5851c916cbcfb5 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a73c04e4819084c0b2ff8e5d2f04 |
completed | April 10, 2026, 7:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f45854b27c81909304aee5e612f934 |
completed | May 1, 2026, 7:37 a.m. |
Created at: April 8, 2026, 9:43 p.m.