Triple
T1823826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fort Wayne Assembly Plant |
E40604
|
entity |
| Predicate | hasSupplierPark |
P31573
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Fort Wayne Assembly Plant, hasSupplierPark, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSupplierPark Context triple: [Fort Wayne Assembly Plant, hasSupplierPark, yes]
-
A.
hasParkOwner
Indicates that an entity serves as the owner or legal controller of a particular park.
-
B.
hasParkArea
Indicates that an entity includes or is associated with a designated park or recreational area within its boundaries.
-
C.
hasParkDistrict
Indicates that an entity is associated with, located within, or administered by a specific park district.
-
D.
hasParks
Indicates that one entity possesses, contains, or is associated with one or more parks.
-
E.
hasBusinessPark
Indicates that one entity possesses, contains, or is associated with a business park as part of its facilities or properties.
- F. None of above. chosen
Provenance (4 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_69a8864644bc8190b2358ab897194ac1 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab21ab83a48190a33afe5db19a21f8 |
completed | March 6, 2026, 6:49 p.m. |
| PD | Predicate disambiguation | batch_69aa61d97d008190b6642aef32eb7e36 |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69ab21aa56108190a5123539d5020741 |
completed | March 6, 2026, 6:49 p.m. |
Created at: March 4, 2026, 7:32 p.m.