Triple
T34660623
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hazzard County, Georgia |
E890095
|
entity |
| Predicate | hasFictionalFarm |
P57125
|
FINISHED |
| Object | Duke farm |
—
|
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: Duke farm | Statement: [Hazzard County, Georgia, hasFictionalFarm, Duke farm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalFarm Context triple: [Hazzard County, Georgia, hasFictionalFarm, Duke farm]
-
A.
hasFictionalAgriculturalCharacter
Indicates that an entity features or includes a character associated with agriculture within a fictional context.
-
B.
hasNotableFarm
chosen
Indicates that an entity possesses or is associated with a farm that is considered notable or significant in some recognized way.
-
C.
hasFarm
Indicates that one entity owns, operates, or is responsible for a farm associated with another entity.
-
D.
hasFictionalPet
Indicates that an entity has, owns, or is associated with a pet that is fictional or imaginary.
-
E.
hasFictionalMine
Indicates that an entity possesses, contains, or is associated with a mine that exists only in 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_69f349d906bc8190b2efd9eff237d94b |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff891e4b9c8190aa86a339a8944496 |
completed | May 9, 2026, 7:21 p.m. |
| PD | Predicate disambiguation | batch_69ff8801180c8190b23e20996ca68e0a |
completed | May 9, 2026, 7:16 p.m. |
Created at: May 1, 2026, 2:04 a.m.