Triple

T34660606

Position	Surface form	Disambiguated ID	Type / Status
Subject	Hazzard County, Georgia	`E890095`	entity
Predicate	hasFictionalGarage	`P30711`	FINISHED
Object	Cooter’s Garage Cooter’s Garage is the fictional auto repair shop run by mechanic Cooter Davenport in the television series "The Dukes of Hazzard."	`E2107020`	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: Cooter’s Garage | Statement: [Hazzard County, Georgia, hasFictionalGarage, Cooter’s Garage]

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: Cooter’s Garage
Triple: [Hazzard County, Georgia, hasFictionalGarage, Cooter’s Garage]

Generated description

Cooter’s Garage is the fictional auto repair shop run by mechanic Cooter Davenport in the television series "The Dukes of Hazzard."

PD Predicate disambiguation gpt-5-mini-2025-08-07

Target predicate: hasFictionalGarage
Context triple: [Hazzard County, Georgia, hasFictionalGarage, Cooter’s Garage]

A. hasGarage chosen
Indicates that one entity possesses or includes a garage associated with it.
B. hasFictionalGasStation
Indicates that one entity includes, features, or is associated with a fictional gas station.
C. hasFictionalDriver
Indicates that an entity (such as a vehicle or object) is associated with a driver who is a fictional or imaginary character.
D. hasFictionalVehicle
Indicates that one entity possesses, controls, or is associated with a vehicle that exists only in a fictional or imaginary context.
E. hasFictionalProprietor
Indicates that something is owned, managed, or run by a fictional character or entity within a narrative 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_69ff7eb7189c81909a8f73fbc4c48e02`	completed	May 9, 2026, 6:36 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_69ff7e54e11081908fb5ce10c5aa7b53`	completed	May 9, 2026, 6:35 p.m.

Created at: May 1, 2026, 2:04 a.m.