Triple
T27845486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belgrano Railway |
E703809
|
entity |
| Predicate | historicalGaugeType |
P39342
|
FINISHED |
| Object | narrow-gauge railway |
—
|
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: narrow-gauge railway | Statement: [Belgrano Railway, historicalGaugeType, narrow-gauge railway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicalGaugeType Context triple: [Belgrano Railway, historicalGaugeType, narrow-gauge railway]
-
A.
historicalGauge
Indicates that one entity serves as a gauge, measure, or reference point for understanding the historical state, level, or condition of another entity.
-
B.
historicalType
Indicates that one entity classifies or characterizes another in terms of its role, status, or category within a historical context.
-
C.
gaugeType
chosen
Indicates the specific kind or category of gauge associated with an entity or measurement.
-
D.
historicallyMeasuredBy
Indicates that one quantity, property, or phenomenon was traditionally or formerly quantified or assessed using a particular measurement method, unit, or instrument.
-
E.
historicalValue
Indicates that something possesses significance, importance, or relevance due to its connection with past events, periods, or developments.
- 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_69fd8e5f7c4c8190ab8e2f2a7bb1bd79 |
completed | May 8, 2026, 7:18 a.m. |
| PD | Predicate disambiguation | batch_69fd8d8a16f08190b9e880901bfa44fe |
completed | May 8, 2026, 7:15 a.m. |
Created at: April 27, 2026, 6:06 p.m.