Triple

T23898186

Position	Surface form	Disambiguated ID	Type / Status
Subject	Scott Turow	`E600962`	entity
Predicate	hasPartInUniverse	`P15645`	FINISHED
Object	Kindle County Kindle County is a fictional Midwestern U.S. jurisdiction that serves as the primary legal and political setting for many of Scott Turow’s courtroom novels.	`E1634414`	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: Kindle County | Statement: [Scott Turow, hasPartInUniverse, Kindle County]

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: Kindle County
Triple: [Scott Turow, hasPartInUniverse, Kindle County]

Generated description

Kindle County is a fictional Midwestern U.S. jurisdiction that serves as the primary legal and political setting for many of Scott Turow’s courtroom novels.

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

Target predicate: hasPartInUniverse
Context triple: [Scott Turow, hasPartInUniverse, Kindle County]

A. hasFictionalUniverseElement chosen
Indicates that one entity is a component, feature, or constituent part of the fictional universe represented by the other entity.
B. hasInUniverseInhabitants
Indicates that a universe or fictional setting contains certain beings or populations as its inhabitants.
C. hasInUniverseLocationRelation
Indicates a relationship where an entity is associated with, or situated at, a specific location within a fictional or defined universe or setting.
D. inUniverse
Indicates that one entity exists, occurs, or is set within the fictional or conceptual universe defined by another entity.
E. hasFictionalUniverseProperty
Indicates that a fictional universe possesses a specific characteristic, attribute, or property.
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_69e295341ac0819080647f2908af793c`	completed	April 17, 2026, 8:16 p.m.
NER	Named-entity recognition	`batch_69f1cddb3fdc819096dc84a1774d9bee`	completed	April 29, 2026, 9:22 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a0fe334e06481908a0918de150bc01c`	completed	May 22, 2026, 5:01 a.m.
NEDg	Description generation	`batch_6a0fe44e2f9c8190a16f81052341c70a`	completed	May 22, 2026, 5:06 a.m.
NED2	Entity disambiguation (via description)	`batch_6a0fe4e5d698819092a5d1b75f213ca0`	completed	May 22, 2026, 5:08 a.m.
PD	Predicate disambiguation	`batch_69f1614e24b48190a1c8fb5b7c75ee0f`	completed	April 29, 2026, 1:39 a.m.

Created at: April 17, 2026, 8:25 p.m.