Triple
T11360017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hörby |
E269060
|
entity |
| Predicate | hasTraditionalTownCharacter |
P86771
|
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: [Hörby, hasTraditionalTownCharacter, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTraditionalTownCharacter Context triple: [Hörby, hasTraditionalTownCharacter, yes]
-
A.
containsTraditionalCity
Indicates that one entity geographically or administratively includes or encompasses a traditional city within its boundaries.
-
B.
hasTraditionalSettlementType
chosen
Indicates that an entity is associated with a specific traditional or historically established type of human settlement (e.g., village, town, hamlet).
-
C.
hasTraditionalCotswoldCharacter
Indicates that something exhibits the typical aesthetic, architectural, or cultural qualities associated with traditional Cotswold style.
-
D.
hasTraditionalParish
Indicates that an entity is associated with or belongs to a specific traditional parish.
-
E.
containsHistoricTown
Indicates that one entity geographically includes or encompasses a town that has recognized historical significance.
- 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_69d6aacbe18081909e5fadb50082dd96 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d800160a1c81909d115bf89fe54a49 |
completed | April 9, 2026, 7:37 p.m. |
| PD | Predicate disambiguation | batch_69d7e7022d508190996f9be0847c2b41 |
completed | April 9, 2026, 5:50 p.m. |
Created at: April 8, 2026, 9:33 p.m.