Triple
T24906010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tex-Mex |
E623709
|
entity |
| Predicate | hasParentRailroad |
P76977
|
FINISHED |
| Object | Kansas City Southern |
—
|
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: Kansas City Southern | Statement: [Tex-Mex, hasParentRailroad, Kansas City Southern]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParentRailroad Context triple: [Tex-Mex, hasParentRailroad, Kansas City Southern]
-
A.
hasRailroadHistoryWith
Indicates a historical relationship or connection between entities involving railroads, such as shared development, operation, or significant events in railway history.
-
B.
hasRail
Indicates that something is equipped with, includes, or is connected to a rail or rail system.
-
C.
hasPrivateRailway
Indicates that an entity owns or operates a railway line that is privately controlled rather than part of a public or national rail system.
-
D.
relatedRailroad
chosen
Indicates that there is an association or connection between an entity and a specific railroad, such as ownership, operation, service, or historical linkage.
-
E.
hasRailroadHistory
Indicates that an entity is associated with, involved in, or notable for historical events, operations, or developments related to railroads.
- 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_69e2fac797cc8190b30d77f4121099ac |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f55e519978819087a1676564a74630 |
completed | May 2, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69f4a0edd10c81908a052ab864d57c54 |
completed | May 1, 2026, 12:47 p.m. |
Created at: April 18, 2026, 5:27 a.m.