Triple
T7417215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neyagawa |
E171159
|
entity |
| Predicate | hasSisterCity |
P919
|
FINISHED |
| Object | Paju |
E226748
|
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: Paju | Statement: [Neyagawa, hasSisterCity, Paju]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paju Context triple: [Neyagawa, hasSisterCity, Paju]
-
A.
Paju
chosen
Paju is a city in South Korea near the Demilitarized Zone, known for its historical sites, cultural complexes, and role as a border hub with North Korea.
-
B.
Balgüe
Balgüe is a small rural village on Ometepe Island in Lake Nicaragua, known for its scenic setting near volcanic landscapes and eco-tourism lodges.
-
C.
Soreang
Soreang is a suburban district and the administrative center of Bandung Regency in West Java, Indonesia, situated within the greater Bandung metropolitan area.
-
D.
Ungjin
Ungjin was an ancient city in the Korean kingdom of Baekje that served as one of its historical capitals and a key political and cultural center.
-
E.
Sokcho
Sokcho is a coastal city in northeastern South Korea known for its beaches, seafood, and proximity to Seoraksan National Park.
- 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_69c68a618bdc81908d8018edadecd1a4 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f2c7ae0c8190a8348d6223aeeecc |
completed | March 27, 2026, 9:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8277c92788190bcd36cfa461b4d95 |
completed | March 28, 2026, 7:09 p.m. |
Created at: March 27, 2026, 3:11 p.m.