Triple

T30854936
Position Surface form Disambiguated ID Type / Status
Subject Crosstown Highway E785893 entity
Predicate hasAbbreviation P43 FINISHED
Object Trunk Highway 62
Trunk Highway 62 is a major east–west freeway in the Minneapolis–Saint Paul metropolitan area of Minnesota, commonly known as the Crosstown Highway.
 E1934710 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: Trunk Highway 62 | Statement: [Crosstown Highway, hasAbbreviation, Trunk Highway 62]
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: Trunk Highway 62
Triple: [Crosstown Highway, hasAbbreviation, Trunk Highway 62]
Generated description
Trunk Highway 62 is a major east–west freeway in the Minneapolis–Saint Paul metropolitan area of Minnesota, commonly known as the Crosstown Highway.

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_69f224b91c14819084e764832fe67a57 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f6917f924481909449b790ae38a271 completed May 3, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_6a28bbfc88148190a2113f655d70145c completed June 10, 2026, 1:21 a.m.
NEDg Description generation batch_6a28bfe8b0708190a67937771c70fd8e completed June 10, 2026, 1:37 a.m.
NED2 Entity disambiguation (via description) batch_6a28c05f27288190ad1e9108f289cfac completed June 10, 2026, 1:39 a.m.
Created at: April 29, 2026, 8:46 p.m.