Triple

T28118550
Position Surface form Disambiguated ID Type / Status
Subject Darlene Love E710709 entity
Predicate performedOn P270 FINISHED
Object (Today I Met) The Boy I’m Gonna Marry
"(Today I Met) The Boy I’m Gonna Marry" is a 1963 Phil Spector-produced pop song, celebrated as one of Darlene Love’s signature recordings and a classic of the girl group era.
E1801890 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: (Today I Met) The Boy I’m Gonna Marry | Statement: [Darlene Love, performedOn, (Today I Met) The Boy I’m Gonna Marry]
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: (Today I Met) The Boy I’m Gonna Marry
Triple: [Darlene Love, performedOn, (Today I Met) The Boy I’m Gonna Marry]
Generated description
"(Today I Met) The Boy I’m Gonna Marry" is a 1963 Phil Spector-produced pop song, celebrated as one of Darlene Love’s signature recordings and a classic of the girl group era.

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_69ef9b72f63081909dfbc2c1ddae86c6 completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f640f6569081909b9aff26d85bc8c2 completed May 2, 2026, 6:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15c9310d9c81909e0c28fccc08061e completed May 26, 2026, 4:24 p.m.
NEDg Description generation batch_6a15cac6172c8190b677d538dee18fb0 completed May 26, 2026, 4:31 p.m.
NED2 Entity disambiguation (via description) batch_6a15cb48691081909c5dde3e9a0db8f4 completed May 26, 2026, 4:33 p.m.
Created at: April 27, 2026, 9:15 p.m.