Triple
T17777182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Punilla |
E443801
|
entity |
| Predicate | hasCapital |
P204
|
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, hasCapital, San Carlos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: San Carlos Context triple: [Punilla, hasCapital, San Carlos]
-
A.
San Carlos
San Carlos is a barangay (village-level administrative division) within the municipality of Mariveles in the province of Bataan, Philippines.
-
B.
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.
-
C.
San Carlos
San Carlos is a city in San Mateo County, California, located on the San Francisco Peninsula between Belmont and Redwood City.
-
D.
San Carlos
San Carlos is a Nicaraguan town that serves as a key river and lake port near the southeastern end of Lake Nicaragua.
-
E.
San Carlos
chosen
San Carlos is a Chilean city known as an agricultural and commercial center in the Ñuble 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_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.