Triple
T21975315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Bulacan |
E542689
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | San Rafael |
—
|
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 Rafael | Statement: [Province of Bulacan, hasMunicipality, San Rafael]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: San Rafael Context triple: [Province of Bulacan, hasMunicipality, San Rafael]
-
A.
San Rafael
chosen
San Rafael is a landlocked agricultural municipality in the province of Bulacan in the Philippines, known for its historical sites and growing suburban communities.
-
B.
San Rafael
San Rafael is a small rural municipality in Chile’s Maule Region, known for its agricultural activities and proximity to the regional capital, Talca.
-
C.
San Rafael
San Rafael is a barangay (village-level administrative division) within the municipality of San Felipe in the province of Zambales, Philippines.
-
D.
San Rafael
San Rafael is a barangay (village-level administrative division) within the municipality of San Antonio in the province of Zambales, Philippines.
-
E.
San Rafael
San Rafael is a small unincorporated community located in Conejos County in southern Colorado, known for its rural setting near the San Luis Valley.
- 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_69e0c48070988190909db97667b9a0ac |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f12487a1a88190abb8a51fcd533b6a |
completed | April 28, 2026, 9:20 p.m. |
Created at: April 16, 2026, 8:03 p.m.