Triple
T20353756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Umaria railway station |
E496086
|
entity |
| Predicate | hasTicketCounter |
P3383
|
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: [Umaria railway station, hasTicketCounter, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTicketCounter Context triple: [Umaria railway station, hasTicketCounter, yes]
-
A.
hasTicketing
chosen
Indicates that an entity provides or is associated with a system or mechanism for issuing, managing, or selling tickets.
-
B.
hasTicketBarrier
Indicates that an access-controlled barrier or gate is present, typically requiring a valid ticket or pass to pass through.
-
C.
hasTicketInspection
Indicates that a ticket is checked or verified by an authorized inspector or system.
-
D.
hasCheckInCounters
Indicates that an entity is associated with one or more check-in counters used for processing arrivals or registrations.
-
E.
hasTicketHall
Indicates that a place or facility includes or is equipped with a designated ticket hall area for purchasing or validating tickets.
- 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_69e0b4a3f7f48190b37f354574028ca6 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67851c7088190ba960a33c6dfa824 |
completed | April 20, 2026, 7:02 p.m. |
| PD | Predicate disambiguation | batch_69e57636b4808190bc2855af48a3ccdc |
completed | April 20, 2026, 12:41 a.m. |
Created at: April 16, 2026, 11:25 a.m.