Triple
T17376660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sierra (Peru) |
E422453
|
entity |
| Predicate | majorCity |
P316
|
FINISHED |
| Object | Puno |
—
|
NE NERFINISHED |
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: Puno | Statement: [Sierra (Peru), majorCity, Puno]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Puno Context triple: [Sierra (Peru), majorCity, Puno]
-
A.
Puno
chosen
Puno is a city in southeastern Peru on the shores of Lake Titicaca, known as a cultural center of the Andean highlands and a gateway to the lake’s islands.
-
B.
Paruro
Paruro is a small town in the Cusco Region of Peru that serves as the administrative and political center of Paruro Province.
-
C.
Cuyoño
Cuyoño is an Austronesian language spoken primarily in the Cuyo Islands and parts of Palawan in the Philippines.
-
D.
Juliaca
Juliaca is a major commercial and transportation hub in southern Peru, known for its bustling markets and proximity to Lake Titicaca.
-
E.
Colina
Colina is a commune and city in central Chile known for its growing residential areas and proximity to Santiago in the Santiago Metropolitan Region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889d6535c81908be333c01deaec4e |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a6ddbd081908908b953597977d2 |
completed | April 19, 2026, 2:14 a.m. |
Created at: April 10, 2026, 5:45 a.m.