Triple
T34193219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DBG |
E877168
|
entity |
| Predicate | refersToRailwayStation |
P196158
|
FINISHED |
| Object | Darbhanga Junction railway station |
—
|
NE NERFINISHED |
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: Darbhanga Junction railway station | Statement: [DBG, refersToRailwayStation, Darbhanga Junction railway station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: refersToRailwayStation Context triple: [DBG, refersToRailwayStation, Darbhanga Junction railway station]
-
A.
hasRailwayStationOn
Indicates that a railway station is located on or serves a particular railway line, route, or network segment.
-
B.
hasRailwayStationRole
Indicates that an entity holds or is assigned a specific functional role or capacity within the operation or management of a railway station.
-
C.
connectsToRailStation
Indicates that one entity has a direct link, route, or access connection to a rail station.
-
D.
otherRailwayStation
Indicates a relationship where one railway station is associated with another as a distinct but related station, such as an alternative, nearby, or counterpart station.
-
E.
hasRailwayStation
Indicates that a place or location is served by, or contains, a railway station.
- 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_69f349af20a4819089ac24d28f2d8112 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fe0d165a48819098b854318a50d76c |
completed | May 8, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69fe0931002481908a95b34f95e9f64e |
completed | May 8, 2026, 4:02 p.m. |
| PDg | Predicate description generation | batch_69fe0d14778c8190986fa4f37f992a2f |
completed | May 8, 2026, 4:19 p.m. |
Created at: May 1, 2026, 1:55 a.m.