Triple

T26379513
Position Surface form Disambiguated ID Type / Status
Subject IL 83 E660984 entity
Predicate isNumberedAfter P4527 FINISHED
Object Illinois Route 82
Illinois Route 82 is a north–south state highway in Illinois that runs through rural areas of the state, connecting small communities and intersecting several major east–west routes.
 E1775422 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: Illinois Route 82 | Statement: [IL 83, isNumberedAfter, Illinois Route 82]
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: Illinois Route 82
Triple: [IL 83, isNumberedAfter, Illinois Route 82]
Generated description
Illinois Route 82 is a north–south state highway in Illinois that runs through rural areas of the state, connecting small communities and intersecting several major east–west routes.

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_69ee812a698881908d6a58265995fa39 completed April 26, 2026, 9:18 p.m.
NER Named-entity recognition batch_69f610740cb4819086aa7efc63cf0a9a completed May 2, 2026, 2:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12bbb39e6c819082338d24eaea7fdc completed May 24, 2026, 8:49 a.m.
NEDg Description generation batch_6a12bcf8cd9c81909f9f001e8a1d4a81 completed May 24, 2026, 8:55 a.m.
NED2 Entity disambiguation (via description) batch_6a12bd75c610819081ae1b4f7fedb4cb completed May 24, 2026, 8:57 a.m.
Created at: April 26, 2026, 11:03 p.m.