Triple

T25584355
Position Surface form Disambiguated ID Type / Status
Subject SR 145 (Indiana) E641336 entity
Predicate abbreviation P43 FINISHED
Object State Road 145
State Road 145 is a north–south state highway in southern Indiana that connects several small communities and provides access to Hoosier National Forest and nearby recreational areas.
E1696041 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 Road 145 | Statement: [SR 145 (Indiana), abbreviation, State Road 145]
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 Road 145
Triple: [SR 145 (Indiana), abbreviation, State Road 145]
Generated description
State Road 145 is a north–south state highway in southern Indiana that connects several small communities and provides access to Hoosier National Forest and nearby recreational areas.

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_69e75dc42b588190a98b58e0df359674 completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f968d1608190a09512f4554a0649 completed May 2, 2026, 1:17 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10d9f2122c8190bcaaaf491617537f completed May 22, 2026, 10:34 p.m.
NEDg Description generation batch_6a10dac66f8c81909a4c4f4a2df2ac16 completed May 22, 2026, 10:37 p.m.
NED2 Entity disambiguation (via description) batch_6a10db25668881909028d0293ec4da51 completed May 22, 2026, 10:39 p.m.
Created at: April 21, 2026, 4:15 p.m.