Triple
T30701529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kollam Junction railway station |
E781622
|
entity |
| Predicate | hasLongDistanceConnections |
P193359
|
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: [Kollam Junction railway station, hasLongDistanceConnections, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLongDistanceConnections Context triple: [Kollam Junction railway station, hasLongDistanceConnections, yes]
-
A.
hasLongDistancePathAccess
Indicates that an entity has the ability or right to use a path or route that spans a long distance.
-
B.
hasAverageDistanceBetweenStations
Indicates that there is a specified average distance separating consecutive stations in a network or route.
-
C.
hasLongerReachThan
Indicates that one entity can extend, influence, or physically reach farther than another entity.
-
D.
hasLongDistanceImportance
Indicates that something maintains significant relevance or impact even over large spatial or temporal distances.
-
E.
hasMultipleDistances
Indicates that a relationship or connection involves more than one distinct distance or separation value between the related entities.
- 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_69f224abfcf081909492e64d3cc35262 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fd44474ed48190ac372e4c88d762ed |
completed | May 8, 2026, 2:02 a.m. |
| PD | Predicate disambiguation | batch_69fd41ef28a48190a66959be5c964461 |
completed | May 8, 2026, 1:52 a.m. |
| PDg | Predicate description generation | batch_69fd4445f8c08190bb2dc27e0971c55d |
completed | May 8, 2026, 2:02 a.m. |
Created at: April 29, 2026, 8:34 p.m.