Triple
T115341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Provinces |
E2325
|
entity |
| Predicate | railwayDevelopment |
P522
|
FINISHED |
| Object | served by Great Indian Peninsula Railway |
—
|
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: served by Great Indian Peninsula Railway | Statement: [Central Provinces, railwayDevelopment, served by Great Indian Peninsula Railway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railwayDevelopment Context triple: [Central Provinces, railwayDevelopment, served by Great Indian Peninsula Railway]
-
A.
railroadEngineeringFeature
Indicates a feature, element, or characteristic specifically related to the design, construction, or operation of railroad engineering systems.
-
B.
railwayLine
Indicates that there is a railway line connection or route associated with or passing through the referenced entity.
-
C.
hasRailSystem
chosen
Indicates that an entity possesses or is served by a rail-based transportation system.
-
D.
trains
Indicates that one entity teaches, instructs, or coaches another entity to develop skills, knowledge, or abilities.
-
E.
servedByRailroad
Indicates that a location or facility is provided with transportation or service by a railroad line or company.
- 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_69a2506c5428819085c28a8884790e29 |
completed | Feb. 28, 2026, 2:18 a.m. |
| NER | Named-entity recognition | batch_69a25760af348190bf402089c240887d |
completed | Feb. 28, 2026, 2:48 a.m. |
| PD | Predicate disambiguation | batch_69a2564417848190a8a8a38e97348963 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:24 a.m.