Triple
T14703944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Black Diamond |
E345375
|
entity |
| Predicate | railwayTypeContext |
P14639
|
FINISHED |
| Object | public 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: public railway | Statement: [Black Diamond, railwayTypeContext, public railway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railwayTypeContext Context triple: [Black Diamond, railwayTypeContext, public railway]
-
A.
railSystemType
Indicates the specific category or classification of a rail transportation system that an entity belongs to or operates within.
-
B.
railwayClass
Indicates the specific classification or category assigned to a railway or railway service within a defined system.
-
C.
railwayLineType
chosen
Indicates the specific kind or classification of a railway line associated with an entity (e.g., main line, branch line, high-speed line).
-
D.
railServiceType
Indicates the specific category or type of rail service that applies to the relationship between the involved entities (e.g., local, express, freight).
-
E.
railwayGaugeContext
Indicates the specific track gauge standard or measurement that applies to, or is used in, a given railway-related context.
- 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_69d822e4a8c08190a155df736bb7bc13 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb6071e5c8190bb5509c859135c2d |
completed | April 14, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69de657c57ec8190ae0b9bb79a514566 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:28 a.m.