Triple

T16593392
Position Surface form Disambiguated ID Type / Status
Subject Maine Turnpike E403145 entity
Predicate connectsTo P845 FINISHED
Object Interstate 295
Interstate 295 is a highway in Maine that serves as an alternative route to Interstate 95, bypassing parts of the Maine Turnpike and providing more direct access to coastal and urban areas such as Portland.
E691574 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: Interstate 295 | Statement: [Maine Turnpike, connectsTo, Interstate 295]
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: Interstate 295
Triple: [Maine Turnpike, connectsTo, Interstate 295]
Generated description
Interstate 295 is a highway in Maine that serves as an alternative route to Interstate 95, bypassing parts of the Maine Turnpike and providing more direct access to coastal and urban areas such as Portland.

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_69d883880d0c81908b5fcd454e767b60 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e35d6fcaa48190b1ba7dc3b792041a completed April 18, 2026, 10:31 a.m.
NED1 Entity disambiguation (via context triple) batch_6a118f6b6b8481908df3cb7d7ac8ca93 completed May 23, 2026, 11:28 a.m.
NEDg Description generation batch_6a119053e3b0819092c8e62b5b4ae02a completed May 23, 2026, 11:32 a.m.
NED2 Entity disambiguation (via description) batch_6a1190db5ab48190a5b902fee03abdde completed May 23, 2026, 11:34 a.m.
Created at: April 10, 2026, 5:16 a.m.