Triple
T36111529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Downton, Yorkshire |
E1044510
|
entity |
| Predicate | fictionalCountySeatOf |
P49448
|
FINISHED |
| Object | Crawley family estate |
—
|
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: Crawley family estate | Statement: [Downton, Yorkshire, fictionalCountySeatOf, Crawley family estate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalCountySeatOf Context triple: [Downton, Yorkshire, fictionalCountySeatOf, Crawley family estate]
-
A.
hasFictionalCountySeatRole
chosen
Indicates that an entity serves in the role of county seat within a fictional or imaginary administrative setting.
-
B.
hasFictionalCounty
Indicates that one entity includes, is set in, or is associated with a county that is fictional rather than real.
-
C.
fictionalTownName
Indicates that the entity is associated with the name of a town that exists only in fiction rather than in the real world.
-
D.
fictionalCapital
Indicates that a location serves as the capital city within a fictional or imaginary political or geographic entity.
-
E.
hasFictionalTownBasedOn
Indicates that a fictional town is modeled on, inspired by, or derived from a specific real-world town or location.
- 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_69f76e344a4c8190af3858c6d78ba88f |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ff234f32888190a1d800a3bda432eb |
completed | May 9, 2026, 12:06 p.m. |
| PD | Predicate disambiguation | batch_69ff228ae9a0819083f4b97c10b923f4 |
completed | May 9, 2026, 12:03 p.m. |
Created at: May 3, 2026, 4:08 p.m.