Triple

T4256549
Position Surface form Disambiguated ID Type / Status
Subject I Want You E95987 entity
Predicate performer P1363 FINISHED
Object Common E2160 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: Common | Statement: [I Want You, performer, Common]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Common
Context triple: [I Want You, performer, Common]
  • A. Common chosen
    Common is an American rapper, actor, and activist known for his socially conscious lyrics and influential role in conscious hip-hop.
  • B. Comum
    Comum, known today as Como, is an ancient town in northern Italy near Lake Como that was an important Roman settlement and later a notable medieval and Renaissance center.
  • C. Common Voice
    Common Voice is an open-source, crowdsourced dataset of voice recordings created to help train and improve speech recognition technologies for diverse languages and accents.
  • D. Commons
    Commons is the commonly used abbreviated name for the House of Commons, the lower house of the Parliament of the United Kingdom.
  • E. Normal
    Normal is a central Illinois town best known as the home of Illinois State University and part of the twin-city community with Bloomington.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69b3454095ac81909c2494f7ff294af1 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34ec1971c81908f7a72418efa8bcc completed March 12, 2026, 11:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b78422a88190a67921ee38638ac8 completed March 14, 2026, 7:31 p.m.
Created at: March 12, 2026, 11:06 p.m.