Triple

T29903866
Position Surface form Disambiguated ID Type / Status
Subject Songs in Red and Gray E759481 entity
Predicate hasTrack P3284 FINISHED
Object Song in Red and Gray
"Song in Red and Gray" is the title track from Suzanne Vega’s 2001 album, noted for its introspective lyrics and understated folk-pop style.
 E759481 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: Song in Red and Gray | Statement: [Songs in Red and Gray, hasTrack, Song in Red and Gray]
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: Song in Red and Gray
Triple: [Songs in Red and Gray, hasTrack, Song in Red and Gray]
Generated description
"Song in Red and Gray" is the title track from Suzanne Vega’s 2001 album, noted for its introspective lyrics and understated folk-pop style.

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_69f224600590819085e148a01c056ef6 completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f677311f3881909ccee017947e043b completed May 2, 2026, 10:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2721e3d6588190bffbeb1a9cf79f40 completed June 8, 2026, 8:11 p.m.
NEDg Description generation batch_6a27226c29fc81909e79cb508975bc92 completed June 8, 2026, 8:13 p.m.
NED2 Entity disambiguation (via description) batch_6a27231dfdac8190870ab5105b8c174d completed June 8, 2026, 8:16 p.m.
Created at: April 29, 2026, 6:07 p.m.