Triple
T13229662
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MRT Light Red Line |
E314977
|
entity |
| Predicate | system |
P730
|
FINISHED |
| Object | MRT (Mass Rapid Transit) |
E1000223
|
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 (Mass Rapid Transit) | Statement: [MRT Light Red Line, system, MRT (Mass Rapid Transit)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MRT (Mass Rapid Transit) Context triple: [MRT Light Red Line, system, MRT (Mass Rapid Transit)]
-
A.
MRT subway
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
chosen
MRT is Singapore’s extensive rapid transit rail network that serves as the backbone of the city’s public transportation system.
-
C.
MRT
MRT is the three-letter ISO 3166-1 alpha-3 country code assigned to Mauritania.
-
D.
MRT
MRT is the commonly used abbreviation for the Taipei Metro, the rapid transit system serving Taipei and its surrounding areas.
-
E.
MRT
MRT is a common abbreviation for urban metro or subway systems providing high-capacity public transportation in major cities.
- 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_69d806affc688190a25b6ccc588e9c72 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d336ae08190bfc118cfbefddf84 |
completed | April 10, 2026, 11:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6ff2c07488190ad07c544cca63a7d |
completed | May 3, 2026, 7:54 a.m. |
Created at: April 9, 2026, 9:21 p.m.