Triple
T32510071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Croft family |
E830906
|
entity |
| Predicate | hasFictionalSeat |
P49448
|
FINISHED |
| Object | Surrey, England |
—
|
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: Surrey, England | Statement: [Croft family, hasFictionalSeat, Surrey, England]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalSeat Context triple: [Croft family, hasFictionalSeat, Surrey, England]
-
A.
hasFictionalLocation
Indicates that an entity is associated with, set in, or takes place within a location that exists only in fiction rather than in the real world.
-
B.
hasFictionalLandmark
Indicates that one entity includes, features, or is associated with a landmark that is fictional rather than real.
-
C.
hasFictionalCountySeatRole
chosen
Indicates that an entity serves in the role of county seat within a fictional or imaginary administrative setting.
-
D.
worksAtFictionalPlace
Indicates that an entity is employed at or associated with performing work in a fictional or imaginary location.
-
E.
basedInFictionalLocation
Indicates that an entity’s primary setting, origin, or operations occur in a fictional (non-real) 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_69f3492318348190ba37fb6b5f1d67f4 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fed09a12648190affcd9bacf7ca275 |
completed | May 9, 2026, 6:13 a.m. |
| PD | Predicate disambiguation | batch_69fecf91d6f481908deb60c965c433ed |
completed | May 9, 2026, 6:09 a.m. |
Created at: May 1, 2026, 1 a.m.