Triple
T8257305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sanrio Puroland |
E193101
|
entity |
| Predicate | publicTransitOperator |
P20657
|
FINISHED |
| Object | Tama Monorail |
E193100
|
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: Tama Monorail | Statement: [Sanrio Puroland, publicTransitOperator, Tama Monorail]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tama Monorail Context triple: [Sanrio Puroland, publicTransitOperator, Tama Monorail]
-
A.
Tama Monorail
chosen
Tama Monorail is a straddle-beam monorail line in Tokyo, Japan, providing urban transit service through the Tama area.
-
B.
Tokyo Monorail
Tokyo Monorail is an urban transit line in Tokyo that provides rapid rail service between central Tokyo and Haneda Airport.
-
C.
KL Monorail
KL Monorail is an elevated urban rail line in Kuala Lumpur that provides rapid transit service through the city’s central and commercial districts.
-
D.
Osaka Monorail
Osaka Monorail is a straddle-beam monorail system in Osaka Prefecture, Japan, serving as a major urban transit line linking key suburbs, commercial areas, and transport hubs.
-
E.
Alweg Monorail
The Alweg Monorail is an elevated monorail system in Seattle that became an iconic symbol of mid-20th-century futuristic transportation design.
- 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_69ca82dfad9c8190b8cd18fb89f50f40 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb78fce9308190ac36512e80b06b52 |
completed | March 31, 2026, 7:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd94f9c97881908c6e9f266aba888e |
completed | April 1, 2026, 9:58 p.m. |
Created at: March 30, 2026, 5:49 p.m.