Triple
T34660607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hazzard County, Georgia |
E890095
|
entity |
| Predicate | hasFictionalBar |
P48081
|
FINISHED |
| Object | The Boar’s Nest |
—
|
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: The Boar’s Nest | Statement: [Hazzard County, Georgia, hasFictionalBar, The Boar’s Nest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalBar Context triple: [Hazzard County, Georgia, hasFictionalBar, The Boar’s Nest]
-
A.
hasFictionalPub
chosen
Indicates that an entity features or includes a fictional pub as part of its content, setting, or structure.
-
B.
hasFictionalHotel
Indicates that an entity includes, features, or is associated with a hotel that exists only in fiction rather than in reality.
-
C.
hasFictionalLandmark
Indicates that one entity includes, features, or is associated with a landmark that is fictional rather than real.
-
D.
hasFictionalForm
Indicates that an entity has a counterpart or representation that exists within a fictional or imaginary context.
-
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_69ff7fc835f08190afd1f8129b7a62a2 |
completed | May 9, 2026, 6:41 p.m. |
| PD | Predicate disambiguation | batch_69ff7f2e99ac8190ba372a1358a05a30 |
completed | May 9, 2026, 6:38 p.m. |
Created at: May 1, 2026, 2:04 a.m.