Triple
T9950190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mir Mahbub Ali Khan |
E195308
|
entity |
| Predicate | introducedRailwaysInState |
P91320
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Mir Mahbub Ali Khan, introducedRailwaysInState, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: introducedRailwaysInState Context triple: [Mir Mahbub Ali Khan, introducedRailwaysInState, true]
-
A.
oneOfEarliestRailroadsIn
Indicates that a railroad is among the first railroads established within a specified geographic area or jurisdiction.
-
B.
hasRailSystem
Indicates that an entity possesses or is served by a rail-based transportation system.
-
C.
hasRailroadHistory
Indicates that an entity is associated with, involved in, or notable for historical events, operations, or developments related to railroads.
-
D.
hasRailroadHistoryWith
Indicates a historical relationship or connection between entities involving railroads, such as shared development, operation, or significant events in railway history.
-
E.
servedRailroadsIn
Indicates that an individual or entity provided service or worked in an official capacity for one or more specified railroad companies.
- 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_69ca82e96a108190932bd1fc4acd73a0 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb65a4e6c8190968192a24aad1b7d |
completed | April 2, 2026, 12:20 a.m. |
| PD | Predicate disambiguation | batch_69cd1d97c44081908730071269f07712 |
completed | April 1, 2026, 1:28 p.m. |
| PDg | Predicate description generation | batch_69cd358386f48190833c862b5b8c04b2 |
completed | April 1, 2026, 3:10 p.m. |
Created at: March 30, 2026, 8:45 p.m.