Triple
T27845520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belgrano Railway |
E703809
|
entity |
| Predicate | historicalOperatorType |
P66217
|
FINISHED |
| Object | state-owned railway company |
—
|
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: state-owned railway company | Statement: [Belgrano Railway, historicalOperatorType, state-owned railway company]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicalOperatorType Context triple: [Belgrano Railway, historicalOperatorType, state-owned railway company]
-
A.
hasHistoricalOperator
Indicates that an entity is or has been managed, controlled, or operated by a specific operator at some point in the past.
-
B.
heritageOperatorType
Indicates the specific category or type of operator responsible for managing or running a heritage-related asset or service.
-
C.
historicalType
chosen
Indicates that one entity classifies or characterizes another in terms of its role, status, or category within a historical context.
-
D.
typicalOperatorType
Indicates the usual or most common type or category of operator associated with a given entity or context.
-
E.
heritageOperator
Indicates that an entity operates, manages, or runs a heritage-related site, service, or asset.
- 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_69ef840d9e3c819093615ebff4ec22be |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69fd91a5dad8819093eeeef527027890 |
completed | May 8, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69fd8f65fe9081908902500a3228d935 |
completed | May 8, 2026, 7:23 a.m. |
Created at: April 27, 2026, 6:06 p.m.