Triple
T37626565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Bardstown |
E936226
|
entity |
| Predicate | hasGeographicalTie |
P146651
|
FINISHED |
| Object | Bardstown, Kentucky |
—
|
NE NERFINISHED |
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: Bardstown, Kentucky | Statement: [Old Bardstown, hasGeographicalTie, Bardstown, Kentucky]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGeographicalTie Context triple: [Old Bardstown, hasGeographicalTie, Bardstown, Kentucky]
-
A.
hasGeographicConnectionTo
chosen
Indicates a relationship where two entities are linked through a shared or relevant geographic feature, location, or spatial association.
-
B.
hasTerritorialAssociation
Indicates a relationship where an entity is linked or connected to a specific territory, area, or geographic region.
-
C.
hasGeographicalLocation
Indicates that an entity is situated in, or associated with, a specific geographical place or area.
-
D.
typicalGeographicalAssociation
Indicates a usual or characteristic geographical connection between entities, such as a place commonly associated with a person, group, or phenomenon.
-
E.
hasGeographicType
Indicates that an entity is associated with or classified by a specific type or category of geographic feature or area.
- 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_69f76ed24820819081bafd36e9088701 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fe5c1a502081909d4024e514309c8e |
completed | May 8, 2026, 9:56 p.m. |
| PD | Predicate disambiguation | batch_69fe5a9df21c819087153f5d0bcaa987 |
completed | May 8, 2026, 9:50 p.m. |
Created at: May 3, 2026, 4:18 p.m.