Triple
T7085346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gangtok |
E165059
|
entity |
| Predicate | ISOCode |
P208
|
FINISHED |
| Object | IN-SK-GA |
E541005
|
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: IN-SK-GA | Statement: [Gangtok, ISOCode, IN-SK-GA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: IN-SK-GA Context triple: [Gangtok, ISOCode, IN-SK-GA]
-
A.
IN-SK
chosen
IN-SK is the ISO 3166-2 code representing the Indian state of Sikkim.
-
B.
Gangwon Province
Gangwon Province is a mountainous region in northeastern South Korea known for its natural scenery, ski resorts, and role as a host area for the 2018 Pyeongchang Winter Olympics.
-
C.
Gyeongbuk
Gyeongbuk is a province in eastern South Korea known for its historical sites, cultural heritage, and scenic rural landscapes.
-
D.
Daejeon-yeok
Daejeon-yeok is the romanized Korean name for Daejeon Station, a major railway hub in the city of Daejeon, South Korea.
-
E.
Gwangju, Gyeonggi
Gwangju, Gyeonggi is a city in South Korea known for its blend of suburban residential areas, light industry, and historical sites within the Seoul Capital Area.
- 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_69c6887d98408190912b9580666b0c1d |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e511535c819098f60de54930380f |
completed | March 27, 2026, 8:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c79484a644819091fac0e361f77c91 |
completed | March 28, 2026, 8:42 a.m. |
Created at: March 27, 2026, 2:41 p.m.