Triple
T32653729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shalimar railway station |
E834803
|
entity |
| Predicate | usedAsTerminalFor |
P195149
|
FINISHED |
| Object | premium long-distance 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: premium long-distance trains | Statement: [Shalimar railway station, usedAsTerminalFor, premium long-distance trains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedAsTerminalFor Context triple: [Shalimar railway station, usedAsTerminalFor, premium long-distance trains]
-
A.
usedTerminal
Indicates that an entity made use of or interacted with a particular terminal or endpoint device.
-
B.
TerminalEUsedFor
Indicates that a terminal E is used for a particular purpose, function, or activity.
-
C.
associatedWithTerminal
Indicates that one entity has a defined relationship or linkage to a specific terminal or endpoint within a system or structure.
-
D.
servesTerminal
Indicates that one entity functions as a terminal or endpoint facility that is served or operated by another entity.
-
E.
terminal3Use
Indicates that an entity makes use of or operates from terminal 3 (such as a specific terminal in a facility, station, or airport).
- F. None of above. chosen
Provenance (4 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_69f3492f72248190ba42fa596aea50e1 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fda94697c4819081291967202248be |
completed | May 8, 2026, 9:13 a.m. |
| PD | Predicate disambiguation | batch_69fda5973fcc8190a57daef31fb70a49 |
completed | May 8, 2026, 8:57 a.m. |
| PDg | Predicate description generation | batch_69fda945e1e08190bf923fcd4d2c548a |
completed | May 8, 2026, 9:13 a.m. |
Created at: May 1, 2026, 1:08 a.m.