Triple

T11426599
Position Surface form Disambiguated ID Type / Status
Subject Anderson metropolitan area E270766 entity
Predicate hasTransportation P105 FINISHED
Object U.S. Route 76
U.S. Route 76 is a major east–west U.S. Highway running across the southeastern United States, connecting communities in states such as Tennessee, Georgia, and South Carolina.
E1649690 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: U.S. Route 76 | Statement: [Anderson metropolitan area, hasTransportation, U.S. Route 76]
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: U.S. Route 76
Triple: [Anderson metropolitan area, hasTransportation, U.S. Route 76]
Generated description
U.S. Route 76 is a major east–west U.S. Highway running across the southeastern United States, connecting communities in states such as Tennessee, Georgia, and South Carolina.

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_69d6aadeef688190874bcecd88b3dd9b completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d806c000b88190bfaa646b2dc424b7 completed April 9, 2026, 8:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a101bc12108819096423d21e6d438a3 completed May 22, 2026, 9:02 a.m.
NEDg Description generation batch_6a102367c6e0819092a483e21fc5cc6c completed May 22, 2026, 9:35 a.m.
NED2 Entity disambiguation (via description) batch_6a10243c77748190a556b0e26d9a2a1c completed May 22, 2026, 9:39 a.m.
Created at: April 8, 2026, 9:35 p.m.