Triple

T23404154
Position Surface form Disambiguated ID Type / Status
Subject Wheeling metropolitan area E559587 entity
Predicate transportationCorridor P385 FINISHED
Object Interstate 470
Interstate 470 is an auxiliary Interstate Highway that serves as a bypass and connector route around the Wheeling metropolitan area in West Virginia and Ohio.
E2234609 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: Interstate 470 | Statement: [Wheeling metropolitan area, transportationCorridor, Interstate 470]
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: Interstate 470
Triple: [Wheeling metropolitan area, transportationCorridor, Interstate 470]
Generated description
Interstate 470 is an auxiliary Interstate Highway that serves as a bypass and connector route around the Wheeling metropolitan area in West Virginia and Ohio.

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_69e24549610c8190a069d6411ce5f661 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f1a4e27db88190b37375b38073291c completed April 29, 2026, 6:27 a.m.
NED1 Entity disambiguation (via context triple) batch_6a40a7d31d908190b1381f3c5680f798 completed June 28, 2026, 4:49 a.m.
NEDg Description generation batch_6a40a991095c8190a77e79a757e7ea95 completed June 28, 2026, 4:56 a.m.
NED2 Entity disambiguation (via description) batch_6a40a9ffe2688190ad8c76e103b9eace completed June 28, 2026, 4:58 a.m.
Created at: April 17, 2026, 5:37 p.m.