Triple
T3182537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samar Province |
E66623
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Catbalogan |
E437409
|
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: Catbalogan | Statement: [Samar Province, capital, Catbalogan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Catbalogan Context triple: [Samar Province, capital, Catbalogan]
-
A.
Catbalogan
chosen
Catbalogan is a coastal city in the Philippines that serves as the capital and commercial hub of Samar province.
-
B.
Tagbilaran
Tagbilaran is a coastal city on Bohol Island in the central Philippines, known as the province’s capital and a key hub for tourism and commerce in the Visayas region.
-
C.
Calbayog
Calbayog is a coastal city in the province of Samar in the Philippines, known as a regional hub for trade, culture, and transportation in Eastern Visayas.
-
D.
Surigao City
Surigao City is a coastal city in the Caraga region of northeastern Mindanao in the Philippines, known as the “City of Island Adventures” for its numerous islands, beaches, and marine attractions.
-
E.
Danao City
Danao City is a component city in the province of Cebu in the Philippines, known historically for its gun-making industry and as a growing commercial and industrial hub in the region.
- 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_69ad8587c1bc8190a2595f2c22ee1001 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada6bd07888190b680eace8290d821 |
completed | March 8, 2026, 4:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b636ee2ed88190b37c7f6027d7623b |
completed | March 15, 2026, 4:34 a.m. |
Created at: March 8, 2026, 3:06 p.m.