Triple
T35703802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Farmington precinct |
E1031658
|
entity |
| Predicate | buildingTypeFictional |
P1844
|
FINISHED |
| Object | converted church |
—
|
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: converted church | Statement: [Farmington precinct, buildingTypeFictional, converted church]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: buildingTypeFictional Context triple: [Farmington precinct, buildingTypeFictional, converted church]
-
A.
fictionalBuilding
Indicates that a building is imaginary or exists only within a fictional or invented context.
-
B.
hasFictionalEstablishmentType
Indicates that an establishment is associated with a particular type or category of fictional setting or institution.
-
C.
buildingType
chosen
Indicates the specific category or function that characterizes what kind of building something is.
-
D.
partOfFictionalCityInfrastructure
Indicates that something is a component or subsystem within the constructed infrastructure of a fictional city.
-
E.
fictionalResidence
Indicates that one entity is the place where another entity lives or is based within a fictional or imaginary context.
- 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_69f76e0d393c8190b6303c64408736db |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a34f8ee08190a040304635539a8f |
completed | May 3, 2026, 7:34 p.m. |
| PD | Predicate disambiguation | batch_69f7a06f125c8190843af194f042a465 |
completed | May 3, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:05 p.m.