Triple

T31010937
Position Surface form Disambiguated ID Type / Status
Subject John Barlow Jarvis E790205 entity
Predicate notableWork P4 FINISHED
Object If I Didn’t Have You in My World
"If I Didn’t Have You in My World" is a country song written by John Barlow Jarvis, best known for being recorded and popularized by Vince Gill.
 E1942081 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: If I Didn’t Have You in My World | Statement: [John Barlow Jarvis, notableWork, If I Didn’t Have You in My World]
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: If I Didn’t Have You in My World
Triple: [John Barlow Jarvis, notableWork, If I Didn’t Have You in My World]
Generated description
"If I Didn’t Have You in My World" is a country song written by John Barlow Jarvis, best known for being recorded and popularized by Vince Gill.

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_69f224c73ca48190a1e46cb58ad4045b completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f694851674819098df826dde29813f completed May 3, 2026, 12:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a29183c165081909ebc5af53fb3d8ee completed June 10, 2026, 7:54 a.m.
NEDg Description generation batch_6a29190c5f6c8190881d5c2b5ebbd64c completed June 10, 2026, 7:58 a.m.
NED2 Entity disambiguation (via description) batch_6a29199ab674819099331e028cf6d811 completed June 10, 2026, 8 a.m.
Created at: April 29, 2026, 8:57 p.m.