Triple
T3461578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jianguomen station |
E73036
|
entity |
| Predicate | hasFareCollectionSystem |
P1973
|
FINISHED |
| Object | automatic fare gates |
—
|
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: automatic fare gates | Statement: [Jianguomen station, hasFareCollectionSystem, automatic fare gates]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFareCollectionSystem Context triple: [Jianguomen station, hasFareCollectionSystem, automatic fare gates]
-
A.
fareSystem
Indicates a relationship where a system is used to determine, collect, or manage fares or payments for transportation or similar services.
-
B.
hasFareControlIntegrationSince
Indicates that a fare control system has been integrated with another system or entity starting from a specific point in time.
-
C.
hasFaregates
chosen
Indicates that an entity is equipped with or contains faregates used to control or validate access, typically for paid entry.
-
D.
airTrainFareCollection
Indicates a relationship where fares for an air train service are collected from passengers or through a designated payment system.
-
E.
hasFareZone
Indicates that an entity is located within or associated with a specific fare zone used for pricing or ticketing.
- 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_69ad85b224d481908ff8be51338d24ff |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbae745e081909007cd3a664c57f3 |
completed | March 8, 2026, 6:07 p.m. |
| PD | Predicate disambiguation | batch_69adae05bb0081909dc7e4779d6e05ef |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:17 p.m.