Triple

T37092821
Position Surface form Disambiguated ID Type / Status
Subject Dierks Bentley E918471 entity
Predicate notableWork P4 FINISHED
Object Free and Easy (Down the Road I Go)
"Free and Easy (Down the Road I Go)" is a hit country song by American singer Dierks Bentley, known for its upbeat, carefree theme and radio success in the mid-2000s.
E2212827 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: Free and Easy (Down the Road I Go) | Statement: [Dierks Bentley, notableWork, Free and Easy (Down the Road I Go)]
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: Free and Easy (Down the Road I Go)
Triple: [Dierks Bentley, notableWork, Free and Easy (Down the Road I Go)]
Generated description
"Free and Easy (Down the Road I Go)" is a hit country song by American singer Dierks Bentley, known for its upbeat, carefree theme and radio success in the mid-2000s.

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_69f76e9a48bc8190a3947508d8bca408 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fb2fd154b881909bef654d8699e375 completed May 6, 2026, 12:10 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3efdccd1d481908cd8b4b9668edb22 completed June 26, 2026, 10:31 p.m.
NEDg Description generation batch_6a3f2329fdd4819081c06dab6d9d7ad4 completed June 27, 2026, 1:11 a.m.
NED2 Entity disambiguation (via description) batch_6a3f251343e8819099d85c22ae02aa9d completed June 27, 2026, 1:19 a.m.
Created at: May 3, 2026, 4:14 p.m.