Triple

T31866579
Position Surface form Disambiguated ID Type / Status
Subject Interstate 395 (Maine) E813471 entity
Predicate abbreviation P43 FINISHED
Object I-395
I-395 is a short auxiliary Interstate Highway in Maine that serves as a connector route to Interstate 95 and the city of Bangor.
E2288701 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: I-395 | Statement: [Interstate 395 (Maine), abbreviation, I-395]
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: I-395
Triple: [Interstate 395 (Maine), abbreviation, I-395]
Generated description
I-395 is a short auxiliary Interstate Highway in Maine that serves as a connector route to Interstate 95 and the city of Bangor.

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_69f348ecb07481909c8f72619131b115 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6b0740e9081908add19702f9cac66 completed May 3, 2026, 2:18 a.m.
NED1 Entity disambiguation (via context triple) batch_6a5acf194508819091f4995b1ae7a1e5 completed July 18, 2026, 12:55 a.m.
NEDg Description generation batch_6a5ad1cd80248190af2b00f6bb01b617 completed July 18, 2026, 1:07 a.m.
NED2 Entity disambiguation (via description) batch_6a5ad3a51f348190a07468a34fbb9074 completed July 18, 2026, 1:15 a.m.
Created at: April 30, 2026, 11:54 p.m.