Triple
T33949512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Leiper Estate |
E870400
|
entity |
| Predicate | hasRailroadInnovation |
P94439
|
FINISHED |
| Object | early experimental railroad |
—
|
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: early experimental railroad | Statement: [Thomas Leiper Estate, hasRailroadInnovation, early experimental railroad]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRailroadInnovation Context triple: [Thomas Leiper Estate, hasRailroadInnovation, early experimental railroad]
-
A.
hasRailroadHistoryWith
Indicates a historical relationship or connection between entities involving railroads, such as shared development, operation, or significant events in railway history.
-
B.
hasRailroadHistory
Indicates that an entity is associated with, involved in, or notable for historical events, operations, or developments related to railroads.
-
C.
hasInnovationType
chosen
Indicates that an entity is associated with, or classified by, a specific type or category of innovation.
-
D.
hasRailSystem
Indicates that an entity possesses or is served by a rail-based transportation system.
-
E.
hasRail
Indicates that something is equipped with, includes, or is connected to a rail or rail system.
- 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_69f3499b0dd48190b07b4b60babcee02 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fcf36d2894819089b7db8e91b63c9d |
completed | May 7, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69fcf25c0a108190bfa823474098640b |
completed | May 7, 2026, 8:13 p.m. |
Created at: May 1, 2026, 1:49 a.m.