Triple
T23991065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lees station |
E605067
|
entity |
| Predicate | fareGatesPresent |
P1973
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Lees station, fareGatesPresent, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fareGatesPresent Context triple: [Lees station, fareGatesPresent, yes]
-
A.
hasFaregates
chosen
Indicates that an entity is equipped with or contains faregates used to control or validate access, typically for paid entry.
-
B.
fareControl
Indicates that an entity is responsible for monitoring, enforcing, or managing payment of fares for access to a service or facility.
-
C.
numberOfGates
Indicates the quantity of gates associated with or belonging to an entity.
-
D.
hasGateNumber
Indicates that an entity (such as a flight or departure) is associated with a specific gate number.
-
E.
hasBoardingGatesFor
Indicates that a location or facility provides designated boarding gates used for embarking passengers onto specific transportation services (such as flights or trains).
- 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_69e295463f7c8190b1c19dbd114641b9 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d38b37648190afb003cded3a7484 |
completed | April 29, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69f1615994c48190a5de95d3f7e5cd0a |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 9:37 p.m.