Triple
T15228761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silang |
E363943
|
entity |
| Predicate | neighboringMunicipality |
P17964
|
FINISHED |
| Object | Indang |
E363938
|
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: Indang | Statement: [Silang, neighboringMunicipality, Indang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Indang Context triple: [Silang, neighboringMunicipality, Indang]
-
A.
Indang
chosen
Indang is a landlocked agricultural municipality in the province of Cavite in the Philippines, known for its coffee, coconut, and relatively cool climate.
-
B.
Mandalong
Mandalong is a small rural locality in the Central Coast region of New South Wales, Australia, known for its bushland setting and semi-rural residential properties.
-
C.
Tagbina
Tagbina is a rural municipality in the province of Surigao del Sur in the Caraga region of Mindanao, Philippines.
-
D.
Sarangani
Sarangani is a coastal province in the southern Philippines known for its rich marine biodiversity, tuna industry, and diverse indigenous cultures.
-
E.
Itang
Itang is a town in western Ethiopia that serves as one of the principal urban centers of the Gambela 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_69d85a0ce24c81909c4d3b6475548c95 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0078ccdf48190b34eabd9e24e45a1 |
completed | April 15, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fedd39d42881908f2ad47613e23bfa |
completed | May 9, 2026, 7:07 a.m. |
Created at: April 10, 2026, 3:12 a.m.