Triple

T32714565
Position Surface form Disambiguated ID Type / Status
Subject Ohio State Route 63 E836486 entity
Predicate abbreviation P43 FINISHED
Object State Route 63
State Route 63 is a state highway in southwestern Ohio that connects the city of Monroe with nearby communities and major routes.
 E2296255 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: State Route 63 | Statement: [Ohio State Route 63, abbreviation, State Route 63]
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: State Route 63
Triple: [Ohio State Route 63, abbreviation, State Route 63]
Generated description
State Route 63 is a state highway in southwestern Ohio that connects the city of Monroe with nearby communities and major 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_69f3493446148190819541f3ffe79975 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6c884982c8190a8180dd729cc4f15 completed May 3, 2026, 4:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a8254f9ae248190a370c9cb15d1bd01 completed Aug. 17, 2026, 12:25 a.m.
NEDg Description generation batch_6a82551f906c8190bc2509f4b4451f31 completed Aug. 17, 2026, 12:26 a.m.
NED2 Entity disambiguation (via description) batch_6a825571ad0081908ad631d65cb7dd1d completed Aug. 17, 2026, 12:27 a.m.
Created at: May 1, 2026, 1:11 a.m.