Triple
T7442046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vu Ban District |
E171777
|
entity |
| Predicate | administrativeCenter |
P1474
|
FINISHED |
| Object | Goi town |
E664920
|
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: Goi town | Statement: [Vu Ban District, administrativeCenter, Goi town]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Goi town Context triple: [Vu Ban District, administrativeCenter, Goi town]
-
A.
Goi town
chosen
Goi town is the administrative and political center of Vụ Bản District in Nam Định Province, Vietnam.
-
B.
Gadap Town
Gadap Town is a large suburban and semi-rural administrative area on the outskirts of Karachi, Pakistan, known for its rapidly growing population and mix of urban and agricultural landscapes.
-
C.
Geita town
Geita town is an urban center in northwestern Tanzania that serves as the administrative and commercial hub of the gold-rich Geita Region.
-
D.
Gucun Town
Gucun Town is a suburban township in Shanghai, China, known for its large Gucun Park and residential communities within Baoshan District.
-
E.
Tingri town
Tingri town is a small settlement in Tibet that serves as a traditional stopover and vantage point for climbers and travelers heading toward Mount Everest and other high Himalayan peaks.
- 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_69c68a65402881908f7869368eb746fb |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f36b9a3c81908abcc2a64d3e6061 |
completed | March 27, 2026, 9:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8344d4c408190a72f8f7718957f21 |
completed | March 28, 2026, 8:04 p.m. |
Created at: March 27, 2026, 3:13 p.m.