Triple
T34660607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hazzard County, Georgia |
E890095
|
entity |
| Predicate | hasFictionalBar |
P48081
|
FINISHED |
| Object |
The Boar’s Nest
The Boar’s Nest is the rowdy rural bar and social hangout prominently featured in the television series "The Dukes of Hazzard."
|
E2107021
|
NE FINISHED |
How this triple was built (3 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]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: The Boar’s Nest Triple: [Hazzard County, Georgia, hasFictionalBar, The Boar’s Nest]
Generated description
The Boar’s Nest is the rowdy rural bar and social hangout prominently featured in the television series "The Dukes of Hazzard."
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 (6 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. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3749002278819092de3654d39c20cc |
completed | June 21, 2026, 2:14 a.m. |
| NEDg | Description generation | batch_6a3749d08ff48190b252be336b564065 |
completed | June 21, 2026, 2:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a374dbedf148190bc1b24d470fd2224 |
completed | June 21, 2026, 2:34 a.m. |
| PD | Predicate disambiguation | batch_69ff7f2e99ac8190ba372a1358a05a30 |
completed | May 9, 2026, 6:38 p.m. |
Created at: May 1, 2026, 2:04 a.m.