Triple
T1204639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greater Central Philippine languages |
E25859
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object | Surigaonon |
E101548
|
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: Surigaonon | Statement: [Greater Central Philippine languages, hasMember, Surigaonon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Surigaonon Context triple: [Greater Central Philippine languages, hasMember, Surigaonon]
-
A.
Tinogasta
Tinogasta is a town in northwestern Argentina known for its wine production, hot springs, and location along the Andean mountain routes in Catamarca Province.
-
B.
Ibanag
chosen
Ibanag is an Austronesian language spoken primarily in the Cagayan Valley region of northern Luzon in the Philippines.
-
C.
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.
-
D.
Batabanó
Batabanó is a coastal municipality in western Cuba known for its fishing industry and ferry connections to nearby islands.
-
E.
Calabarzon
Calabarzon is a populous and industrialized region in the southern part of Luzon in the Philippines, known for its mix of urban centers, agricultural areas, and manufacturing hubs.
- 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_69a4942b30f08190a91c60573e16b5ef |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bdc0f8d08190b340012a9eb26275 |
completed | March 1, 2026, 10:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac8a08e1a881908b3f3a41cc1fb010 |
completed | March 7, 2026, 8:26 p.m. |
Created at: March 1, 2026, 7:46 p.m.