Triple
T20069535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Quezon |
E499696
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Gumaca |
—
|
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: Gumaca | Statement: [Province of Quezon, hasMunicipality, Gumaca]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gumaca Context triple: [Province of Quezon, hasMunicipality, Gumaca]
-
A.
Gumaca
chosen
Gumaca is a coastal municipality in the province of Quezon in the Philippines, known for its historic churches and role as a local commercial center.
-
B.
Malibcong
Malibcong is a remote, mountainous municipality in the Philippine province of Abra known for its indigenous communities and largely undeveloped natural landscapes.
-
C.
Sarangani
Sarangani is a coastal province in the southern Philippines known for its rich marine biodiversity, tuna industry, and diverse indigenous cultures.
-
D.
Marawila
Marawila is a coastal town in Sri Lanka known for its beaches, fishing community, and tourism-oriented resorts.
-
E.
Kalamansig
Kalamansig is a coastal municipality in the province of Sultan Kudarat in the Philippines, known for its fishing industry and diverse indigenous communities.
- 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_69da627770948190997f486f9a2e370f |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e664365ad0819089103b00d1cf8c9f |
completed | April 20, 2026, 5:36 p.m. |
Created at: April 11, 2026, 3:39 p.m.