Triple
T35467919
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chicago and North Western Railway corridor |
E1025128
|
entity |
| Predicate | hasReuseType |
P96761
|
FINISHED |
| Object | rail-trail conversion |
—
|
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: rail-trail conversion | Statement: [Chicago and North Western Railway corridor, hasReuseType, rail-trail conversion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReuseType Context triple: [Chicago and North Western Railway corridor, hasReuseType, rail-trail conversion]
-
A.
isReuseOf
Indicates that one entity is derived from, or created by reusing, the content, structure, or components of another entity.
-
B.
hasReconstructionType
Indicates the specific method or category of reconstruction applied to an object, structure, or dataset.
-
C.
hasReclamationType
chosen
Indicates the specific method or category of reclamation associated with an entity, such as how land, materials, or resources are recovered or restored.
-
D.
reusedIn
Indicates that something previously used in one context or instance is used again in another context or instance.
-
E.
haveType
Indicates that an entity belongs to or is classified under a specified type or category.
- 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_69f76dfa20d0819089585dc2cf653aea |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037c8d06cc8190ab6a5e18d9d2571e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0324d08190ac5b610cc0f6a38c |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:04 p.m.