Triple
T21975305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Bulacan |
E542689
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Hagonoy |
—
|
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: Hagonoy | Statement: [Province of Bulacan, hasMunicipality, Hagonoy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hagonoy Context triple: [Province of Bulacan, hasMunicipality, Hagonoy]
-
A.
Hagonoy
chosen
Hagonoy is a coastal municipality in the province of Bulacan in the Philippines, known for its fishing industry and aquaculture.
-
B.
Hagonoy
Hagonoy is a coastal agricultural municipality in the province of Davao del Sur in the Philippines.
-
C.
Ogikubo
Ogikubo is a residential and commercial district in western Tokyo known for its relaxed atmosphere, ramen shops, and role as a transport hub on the Chūō Line.
-
D.
Shuniah
Shuniah is a rural municipality in northwestern Ontario, Canada, located along the northern shore of Lake Superior near Thunder Bay.
-
E.
Hagena
Hagena is a legendary or heroic figure referenced in the Old English poem "Widsith," which catalogs various rulers and warriors known in early Germanic tradition.
- 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.