Triple
T2375881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cebu |
E46197
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Moalboal |
E235324
|
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: Moalboal | Statement: [Cebu, hasPart, Moalboal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moalboal Context triple: [Cebu, hasPart, Moalboal]
-
A.
Moalboal
chosen
Moalboal is a coastal town in the Philippines renowned for its vibrant coral reefs, sardine runs, and popular diving and snorkeling spots.
-
B.
Guihulngan
Guihulngan is a coastal city and commercial hub in the northern part of Negros Oriental in the Philippines.
-
C.
Balamban
Balamban is a coastal municipality in the province of Cebu in the Philippines, known for its shipbuilding industry and growing economic zone.
-
D.
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.
-
E.
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.
- 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_69a88a1554a48190a0180682bcf099be |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abc794eee481908163148e1e666d9b |
completed | March 7, 2026, 6:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b402a702a081909319ba32990fa010 |
completed | March 13, 2026, 12:27 p.m. |
Created at: March 4, 2026, 7:57 p.m.