Triple
T4636654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agno River |
E101547
|
entity |
| Predicate | hasCityOnRiver |
P17819
|
FINISHED |
| Object | Dagupan |
E411021
|
NE FINISHED |
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: Dagupan | Statement: [Agno River, hasCityOnRiver, Dagupan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dagupan Context triple: [Agno River, hasCityOnRiver, Dagupan]
-
A.
Dagupan
chosen
Dagupan is a coastal independent component city in the Philippines known for its bangus (milkfish) industry and role as a commercial and educational center in Pangasinan.
-
B.
Pagadian City
Pagadian City is a coastal city in the southern Philippines that serves as the regional center and administrative hub of the Zamboanga Peninsula.
-
C.
Calapan
Calapan is the capital city of Oriental Mindoro in the Philippines, serving as a key commercial and transportation hub in the Mimaropa region.
-
D.
Iriga City
Iriga City is a component city in the province of Camarines Sur in the Philippines, known for its Mount Iriga volcano and role as a commercial and educational hub in the Bicol Region.
-
E.
Bayugan
Bayugan is a component city in the Caraga region of Mindanao in the Philippines, known as an agricultural and commercial hub in its area.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69bd43d2f1c081908cd4b7ec48ecc73d |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a62a9e48190b0cf1cbcc51f00c0 |
completed | March 20, 2026, 2:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bfdb12f33c819084d9268bd31b1f6c |
completed | March 22, 2026, 12:05 p.m. |
Created at: March 20, 2026, 1:13 p.m.