Triple

T18522977
Position Surface form Disambiguated ID Type / Status
Subject Pulaski County, Indiana E452635 entity
Predicate borderedByCounty P6346 FINISHED
Object Cass County, Indiana
Cass County, Indiana is a county in north-central Indiana known for its county seat of Logansport and its role as a regional hub for transportation and agriculture.
E2106611 NE FINISHED

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: Cass County, Indiana | Statement: [Pulaski County, Indiana, borderedByCounty, Cass County, Indiana]
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: Cass County, Indiana
Triple: [Pulaski County, Indiana, borderedByCounty, Cass County, Indiana]
Generated description
Cass County, Indiana is a county in north-central Indiana known for its county seat of Logansport and its role as a regional hub for transportation and agriculture.

Provenance (5 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_69d8d386df84819092355ebb260d848e completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5338f6da48190bdb374019d10db05 completed April 19, 2026, 7:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3748caf26c8190a94ac703f2914b52 completed June 21, 2026, 2:13 a.m.
NEDg Description generation batch_6a374a91d4f08190bc2df424a4136b3d completed June 21, 2026, 2:21 a.m.
NED2 Entity disambiguation (via description) batch_6a374b44cba88190999dede2bc2a408e completed June 21, 2026, 2:24 a.m.
Created at: April 10, 2026, 11:37 a.m.