Triple
T9483400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | General Santos |
E228700
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Sarangani |
E257340
|
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: Sarangani | Statement: [General Santos, adjacentTo, Sarangani]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sarangani Context triple: [General Santos, adjacentTo, Sarangani]
-
A.
Sarangani
chosen
Sarangani is a coastal province in the southern Philippines known for its rich marine biodiversity, tuna industry, and diverse indigenous cultures.
-
B.
Danao
Danao is a coastal city and municipality on Cebu Island in the Philippines known for its historical significance and local industries.
-
C.
Karagawan
Karagawan is a regional dialect of the Isnag language spoken by the Isnag people of northern Luzon in the Philippines.
-
D.
Maragondon
Maragondon is a historic rural municipality in the province of Cavite in the Philippines, known for its Spanish-era heritage sites and nearby natural attractions.
-
E.
Balamban
Balamban is a coastal municipality in the province of Cebu in the Philippines, known for its shipbuilding industry and growing economic zone.
- 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_69ca84730a5081908de282651019bf2f |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd804c859081908c261ad16b501f0d |
completed | April 1, 2026, 8:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d139f7fa90819092e3fbcc62a9e5b9 |
completed | April 4, 2026, 4:19 p.m. |
Created at: March 30, 2026, 7:55 p.m.