Triple
T12719342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bang Wa Station |
E303932
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
Bang Wa
Bang Wa is a transit station in Bangkok, Thailand, serving as an interchange between the BTS Skytrain and the MRT Blue Line.
|
E1000091
|
NE FINISHED |
How this triple was built (4 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: Bang Wa | Statement: [Bang Wa Station, shortName, Bang Wa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bang Wa Context triple: [Bang Wa Station, shortName, Bang Wa]
-
A.
Ban Pong
Ban Pong is a town in western Thailand that served as a key rail junction and starting point for the World War II–era Burma Railway.
-
B.
Wangtoo
Wangtoo is a small settlement in Himachal Pradesh, India, known primarily for its proximity to the Karcham Wangtoo hydroelectric dam on the Sutlej River.
-
C.
Ban Chang
Ban Chang is a coastal town and district in Rayong Province, eastern Thailand, known for its proximity to major industrial estates and U-Tapao–Rayong–Pattaya International Airport.
-
D.
Hoan-ya
Hoan-ya is an alternative name for the Hoanya language, an indigenous Formosan language historically spoken in Taiwan.
-
E.
Bang Bao
Bang Bao is a small fishing village and pier area on Ko Chang in Thailand, known for its stilt houses, seafood restaurants, and boat tours to nearby islands.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Bang Wa Triple: [Bang Wa Station, shortName, Bang Wa]
Generated description
Bang Wa is a transit station in Bangkok, Thailand, serving as an interchange between the BTS Skytrain and the MRT Blue Line.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bang Wa Target entity description: Bang Wa is a transit station in Bangkok, Thailand, serving as an interchange between the BTS Skytrain and the MRT Blue Line.
-
A.
Ban Pong
Ban Pong is a town in western Thailand that served as a key rail junction and starting point for the World War II–era Burma Railway.
-
B.
Wangtoo
Wangtoo is a small settlement in Himachal Pradesh, India, known primarily for its proximity to the Karcham Wangtoo hydroelectric dam on the Sutlej River.
-
C.
Ban Chang
Ban Chang is a coastal town and district in Rayong Province, eastern Thailand, known for its proximity to major industrial estates and U-Tapao–Rayong–Pattaya International Airport.
-
D.
Hoan-ya
Hoan-ya is an alternative name for the Hoanya language, an indigenous Formosan language historically spoken in Taiwan.
-
E.
Bang Bao
Bang Bao is a small fishing village and pier area on Ko Chang in Thailand, known for its stilt houses, seafood restaurants, and boat tours to nearby islands.
- F. None of above. chosen
Provenance (5 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_69d7bdf084148190ab9d513dc0735af4 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96411d87481909127e81755f23964 |
completed | April 10, 2026, 8:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f67c8250108190bb7b3c93e590ea47 |
completed | May 2, 2026, 10:36 p.m. |
| NEDg | Description generation | batch_69f67db4dd2081909a238e368645e899 |
completed | May 2, 2026, 10:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f67ec570a881909c98471b701999f0 |
completed | May 2, 2026, 10:46 p.m. |
Created at: April 9, 2026, 5:24 p.m.