Triple
T2772234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BTS Skytrain |
E61481
|
entity |
| Predicate | hasDepot |
P2413
|
FINISHED |
| Object |
Mo Chit Depot
Mo Chit Depot is a major maintenance and stabling facility serving Bangkok’s BTS Skytrain system.
|
E297269
|
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: Mo Chit Depot | Statement: [BTS Skytrain, hasDepot, Mo Chit Depot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mo Chit Depot Context triple: [BTS Skytrain, hasDepot, Mo Chit Depot]
-
A.
Wadala Depot
Wadala Depot is a key station and maintenance hub on the Mumbai Monorail network, serving the Wadala area of Mumbai, India.
-
B.
Jangsan Depot
Jangsan Depot is a maintenance and storage facility serving trains on the Busan Metro system in Busan, South Korea.
-
C.
Daejeo Depot
Daejeo Depot is a maintenance and storage facility serving the Busan Metro system in Busan, South Korea.
-
D.
Xilang Depot
Xilang Depot is a maintenance and storage facility serving the Guangzhou Metro system in Guangzhou, China.
-
E.
Jiahewanggang Depot
Jiahewanggang Depot is a major operations and maintenance facility serving Guangzhou Metro’s urban rail network in Guangzhou, China.
- 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: Mo Chit Depot Triple: [BTS Skytrain, hasDepot, Mo Chit Depot]
Generated description
Mo Chit Depot is a major maintenance and stabling facility serving Bangkok’s BTS Skytrain system.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mo Chit Depot Target entity description: Mo Chit Depot is a major maintenance and stabling facility serving Bangkok’s BTS Skytrain system.
-
A.
Wadala Depot
Wadala Depot is a key station and maintenance hub on the Mumbai Monorail network, serving the Wadala area of Mumbai, India.
-
B.
Jangsan Depot
Jangsan Depot is a maintenance and storage facility serving trains on the Busan Metro system in Busan, South Korea.
-
C.
Daejeo Depot
Daejeo Depot is a maintenance and storage facility serving the Busan Metro system in Busan, South Korea.
-
D.
Xilang Depot
Xilang Depot is a maintenance and storage facility serving the Guangzhou Metro system in Guangzhou, China.
-
E.
Jiahewanggang Depot
Jiahewanggang Depot is a major operations and maintenance facility serving Guangzhou Metro’s urban rail network in Guangzhou, China.
- 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_69ab4b7cd13481909174bca9809ed259 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdd6b9cc48190bd9f7d8d33fe1ec1 |
completed | March 7, 2026, 8:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc0528304819081ad54a945acd77a |
completed | March 10, 2026, 6:55 a.m. |
| NEDg | Description generation | batch_69afc1317a648190b8c7fb834a952a95 |
completed | March 10, 2026, 6:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69afc1a64e608190baadbf499e35e73e |
completed | March 10, 2026, 7 a.m. |
Created at: March 6, 2026, 9:57 p.m.