Triple
T11087313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MRT Kajang Line |
E262154
|
entity |
| Predicate | connectsWith |
P37
|
FINISHED |
| Object | Monorail Line |
E721184
|
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: Monorail Line | Statement: [MRT Kajang Line, connectsWith, Monorail Line]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Monorail Line Context triple: [MRT Kajang Line, connectsWith, Monorail Line]
-
A.
Monorail Line
chosen
Monorail Line is a designated route or service classification used within the Tama Monorail system in Japan.
-
B.
Alweg Monorail
The Alweg Monorail is an elevated monorail system in Seattle that became an iconic symbol of mid-20th-century futuristic transportation design.
-
C.
Tama Monorail
Tama Monorail is a straddle-beam monorail line in Tokyo, Japan, providing urban transit service through the Tama area.
-
D.
Pink Line
The Pink Line is a rapid transit route in Chicago's "L" system that runs between the Loop and the city's West Side neighborhoods.
-
E.
Pink Line
Pink Line is a major corridor of the Delhi Metro network that forms part of the system’s orbital route around the city.
- 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_69d6aa9983c08190b0ef61603b69feac |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d799c5008081908f59612243fa4f7a |
completed | April 9, 2026, 12:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3e7a6dfa8819096f822294eb64dd1 |
completed | April 18, 2026, 8:20 p.m. |
Created at: April 8, 2026, 9:27 p.m.