Triple
T1938885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ho Chi Minh City Metro |
E41505
|
entity |
| Predicate | designSpeed |
P2096
|
FINISHED |
| Object | approximately 80 km/h for metro trains |
—
|
LITERAL 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: approximately 80 km/h for metro trains | Statement: [Ho Chi Minh City Metro, designSpeed, approximately 80 km/h for metro trains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: designSpeed Context triple: [Ho Chi Minh City Metro, designSpeed, approximately 80 km/h for metro trains]
-
A.
maxSpeed
chosen
Indicates the greatest possible speed at which an entity can move or operate under specified conditions.
-
B.
hasSpeedLimit
Indicates that a specified maximum allowable speed is imposed on the associated entity or context.
-
C.
speedAchieved
Indicates that a particular speed has been reached or attained by an entity during an event or action.
-
D.
hasSpeedLimitRange
Indicates that there is a specified minimum and maximum speed limit applicable to a given context or segment.
-
E.
speed
Indicates the rate at which an entity moves or changes position over time.
- F. None of above.
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_69a88649b24c819080047f26b6db2ded |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb2c8be648190836580cec77a143f |
completed | March 7, 2026, 5:08 a.m. |
| PD | Predicate disambiguation | batch_69abaff07cf88190b4883c5f17f90abd |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:36 p.m.