Triple
T19036769
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katni Junction |
E465891
|
entity |
| Predicate | hasNearbyRailFacility |
P19495
|
FINISHED |
| Object | New Katni Junction diesel and electric loco sheds |
—
|
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: New Katni Junction diesel and electric loco sheds | Statement: [Katni Junction, hasNearbyRailFacility, New Katni Junction diesel and electric loco sheds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyRailFacility Context triple: [Katni Junction, hasNearbyRailFacility, New Katni Junction diesel and electric loco sheds]
-
A.
hasNearbyRailway
Indicates that one entity is located close to a railway associated with or relevant to another entity.
-
B.
hasNearbyRailwayStation
Indicates that a railway station is located within a short or convenient distance from the referenced entity.
-
C.
hasRailStation
Indicates that one entity possesses, contains, or is served by a rail station.
-
D.
hasRailwayStation
Indicates that a place or location is served by, or contains, a railway station.
-
E.
hasRailFacility
chosen
Indicates that an entity possesses or is served by a rail-related facility, such as a railway station, terminal, or yard.
- 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_69d8dd0359648190bc2a9202c5cf29d2 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d744b39881909334a80a4c15000b |
completed | April 20, 2026, 7:35 a.m. |
| PD | Predicate disambiguation | batch_69e4a3001e388190aa6057266514e75a |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, 12:02 p.m.