Triple
T24745222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NP |
E618676
|
entity |
| Predicate | railroadSuccessor |
P157699
|
FINISHED |
| Object | Burlington Northern Railroad |
—
|
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: Burlington Northern Railroad | Statement: [NP, railroadSuccessor, Burlington Northern Railroad]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railroadSuccessor Context triple: [NP, railroadSuccessor, Burlington Northern Railroad]
-
A.
formerRailroad
Indicates that an entity was previously a railroad but no longer functions as one.
-
B.
railroad
Indicates that one entity constructs, operates, or provides railroad or train transportation services for another entity or area.
-
C.
followsFormerRailroad
Indicates that something is aligned with or traces the route of a former railroad line.
-
D.
relatedRailroad
Indicates that there is an association or connection between an entity and a specific railroad, such as ownership, operation, service, or historical linkage.
-
E.
railroadMet
Indicates that two or more railroads encountered or connected with each other at a specific place or time.
- 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_69e2fab8f95c81908bb9e552cf3280c2 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f44a417a58819081777e18dda149fd |
completed | May 1, 2026, 6:37 a.m. |
| PD | Predicate disambiguation | batch_69f442a977b08190b44eac040cb90211 |
completed | May 1, 2026, 6:05 a.m. |
| PDg | Predicate description generation | batch_69f44a3adb7c8190941572f718b3b93c |
completed | May 1, 2026, 6:37 a.m. |
Created at: April 18, 2026, 4:21 a.m.