Triple
T19031692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Union |
E465754
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Bauang |
E953883
|
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: Bauang | Statement: [La Union, hasMunicipality, Bauang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bauang Context triple: [La Union, hasMunicipality, Bauang]
-
A.
Bauang
chosen
Bauang is a coastal municipality in the province of La Union in the Philippines, known for its beaches and tourism.
-
B.
Tinganes
Tinganes is the historic peninsula in central Tórshavn, Faroe Islands, known as one of the world’s oldest parliamentary meeting places and the seat of the Faroese government.
-
C.
Hisingen
Hisingen is a large island and district in Gothenburg, Sweden, known for its industrial areas, shipyards, and rapidly developing residential and tech hubs.
-
D.
Enebakk
Enebakk is a rural municipality in Viken county, Norway, known for its forests, lakes, and proximity to the Oslo metropolitan area.
-
E.
Bjorli
Bjorli is a Norwegian village known for its ski resort and scenic mountain surroundings in Innlandet county.
- 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_69d8dd0359648190bc2a9202c5cf29d2 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d7410dd08190b08a7c0a2b8d67f3 |
completed | April 20, 2026, 7:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a05be59f0088190ae133c2d12beb2c0 |
completed | May 14, 2026, 12:21 p.m. |
Created at: April 10, 2026, 12:02 p.m.