Triple
T28453432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Corredores Ferroviarios |
E716640
|
entity |
| Predicate | operatedInCountryRailNetwork |
P122655
|
FINISHED |
| Object | Argentine railway network |
—
|
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: Argentine railway network | Statement: [Corredores Ferroviarios, operatedInCountryRailNetwork, Argentine railway network]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatedInCountryRailNetwork Context triple: [Corredores Ferroviarios, operatedInCountryRailNetwork, Argentine railway network]
-
A.
operatesRailNetworkOf
Indicates that one entity manages and runs the rail network belonging to or associated with another entity.
-
B.
railwayOperatorCountry
chosen
Indicates the country in which a given railway operator is based or operates.
-
C.
isNationalRailwaySystemOf
Indicates that one entity functions as the official national railway system serving and operating within the territory of another entity.
-
D.
appliesToRailwayNetwork
Indicates that something is relevant or specifically applicable to a railway network as a whole.
-
E.
railNetworkCountry
Indicates that a rail network is located within, or primarily serves, a specific country.
- 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_69efd6b76f8c8190a7ba908aca280942 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69fe9dfaa2d08190b2084f63f842eb6b |
completed | May 9, 2026, 2:37 a.m. |
| PD | Predicate disambiguation | batch_69fe9bba947c81908b0b2b92a4d19b37 |
completed | May 9, 2026, 2:28 a.m. |
Created at: April 28, 2026, 1:53 a.m.