Triple
T2772155
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chatuchak Weekend Market |
E61479
|
entity |
| Predicate | transportAccess |
P1288
|
FINISHED |
| Object | MRT subway |
E61825
|
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: MRT subway | Statement: [Chatuchak Weekend Market, transportAccess, MRT subway]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MRT subway Context triple: [Chatuchak Weekend Market, transportAccess, MRT subway]
-
A.
MRT subway
chosen
The MRT subway in Bangkok is a major rapid transit system that provides fast, air-conditioned underground and elevated rail services across key areas of the city.
-
B.
MRT
MRT is the three-letter ISO 3166-1 alpha-3 country code assigned to Mauritania.
-
C.
Metro Rail
Metro Rail is the urban rapid transit rail system serving Los Angeles County, providing light rail and subway services across the region.
-
D.
Metro SubwayLink
Metro SubwayLink is Baltimore’s rapid transit subway system, providing high-frequency rail service across key corridors in the Baltimore metropolitan area.
-
E.
Taipei Metro
Taipei Metro is the rapid transit system serving the Taipei metropolitan area, known for its extensive network, punctual service, and cleanliness.
- 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_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. |
Created at: March 6, 2026, 9:57 p.m.