Triple
T32683570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | APM line (Guangzhou Metro) |
E835654
|
entity |
| Predicate | hasTrainOperation |
P62161
|
FINISHED |
| Object | fully automatic train operation |
—
|
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: fully automatic train operation | Statement: [APM line (Guangzhou Metro), hasTrainOperation, fully automatic train operation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrainOperation Context triple: [APM line (Guangzhou Metro), hasTrainOperation, fully automatic train operation]
-
A.
trainOperation
chosen
Indicates that an entity is engaged in operating, running, or managing the movement and service of a train.
-
B.
hasPassengerOperations
Indicates that an entity conducts or supports transportation services specifically for carrying passengers.
-
C.
hasLNGTrain
Indicates that something possesses or is equipped with an LNG (liquefied natural gas) processing or transport train as part of its facilities or infrastructure.
-
D.
hasPlannedTrain
Indicates that an entity is associated with a train that is scheduled or planned to operate, rather than one currently in service.
-
E.
hasPassengerTrains
Indicates that a location, route, or rail line is served by trains that carry passengers.
- 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_69f3493211388190993801216afbc2a7 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69ff17be6ad48190963206f2619b1b28 |
completed | May 9, 2026, 11:17 a.m. |
| PD | Predicate disambiguation | batch_69ff1724ba24819092c928fcbcb286ec |
completed | May 9, 2026, 11:14 a.m. |
Created at: May 1, 2026, 1:09 a.m.