Triple
T17683820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Miguel campus |
E440836
|
entity |
| Predicate | locatedInCity |
P40
|
FINISHED |
| Object | San Miguel |
—
|
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 Miguel | Statement: [San Miguel campus, locatedInCity, San Miguel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: San Miguel Context triple: [San Miguel campus, locatedInCity, San Miguel]
-
A.
San Miguel
San Miguel is a landlocked agricultural municipality in the province of Bulacan in the Philippines, known for its historical sites and rural communities.
-
B.
San Miguel
San Miguel is a municipality located in Colombia’s southern Putumayo Department, near the border with Ecuador.
-
C.
San Miguel
San Miguel is a city in the Greater Buenos Aires metropolitan area of Argentina, located in the northwest of Buenos Aires Province.
-
D.
San Miguel
San Miguel is a city in eastern El Salvador that serves as an important commercial and cultural center for the surrounding region.
-
E.
San Miguel
San Miguel is a lakeside settlement in Guatemala situated on the shores of Lake Petén Itzá, known for its proximity to the historic island city of Flores and nearby Maya archaeological sites.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69d8b9e940b081908b862bb0e6e89b0d |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4704626308190bbdd98d27beb3f24 |
completed | April 19, 2026, 6:03 a.m. |
Created at: April 10, 2026, 10:02 a.m.