Triple
T17777183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Punilla |
E443801
|
entity |
| Predicate | administrativeCenter |
P1474
|
FINISHED |
| Object | San Carlos |
—
|
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: San Carlos | Statement: [Punilla, administrativeCenter, San Carlos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: San Carlos Context triple: [Punilla, administrativeCenter, San Carlos]
-
A.
San Carlos
chosen
San Carlos is a historic town in northwestern Argentina’s Salta Province, known for its colonial architecture, wine production, and role as a cultural hub in the Calchaquí Valleys.
-
B.
San Carlos
San Carlos is a municipality located in the Morazán Department of northeastern El Salvador, known for its rural character and mountainous surroundings.
-
C.
San Carlos
San Carlos is a city in Arizona that lends its name to the nearby San Carlos Dam and is closely associated with the San Carlos Apache Indian Reservation.
-
D.
San Carlos
San Carlos is a barangay (village-level administrative division) within the municipality of Mariveles in the province of Bataan, Philippines.
-
E.
San Carlos
San Carlos is a historic city in southeastern Uruguay known for its colonial heritage and role as a commercial and service center within the Maldonado Department.
- 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_69d8b9ef17708190bdf7e2adbf14ddc2 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4871e06a481909cf6d59e49dc21c5 |
completed | April 19, 2026, 7:41 a.m. |
Created at: April 10, 2026, 10:12 a.m.