Triple

T8444574
Position Surface form Disambiguated ID Type / Status
Subject Oak E199639 entity
Predicate notableWorkWith P26239 FINISHED
Object Jennifer Lopez E68363 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: Jennifer Lopez | Statement: [Oak, notableWorkWith, Jennifer Lopez]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jennifer Lopez
Context triple: [Oak, notableWorkWith, Jennifer Lopez]
  • A. Jennifer Lopez chosen
    Jennifer Lopez is an American singer, actress, and dancer who became a global pop culture icon through her chart-topping music, film roles, and influential performances.
  • B. Christina Aguilera
    Christina Aguilera is an American pop and R&B singer known for her powerful vocal range, soulful performances, and hits like "Genie in a Bottle" and "Beautiful."
  • C. Dayanara Torres
    Dayanara Torres is a Puerto Rican actress, model, and former Miss Universe who gained international fame in the 1990s.
  • D. Emily Estefan
    Emily Estefan is an American singer, songwriter, and producer known for her eclectic musical style and for being the daughter of musicians Gloria and Emilio Estefan.
  • E. Christina Milian
    Christina Milian is an American singer, songwriter, and actress known for early-2000s R&B-pop hits like "Dip It Low" and roles in films such as "Love Don't Cost a Thing."
  • 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_69ca83170f9081909cd98f55614c6476 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe3122cfc8190ac6103fa4e4a7c45 completed March 31, 2026, 3:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce1dac8cb08190b74985a6ba3c938f completed April 2, 2026, 7:41 a.m.
Created at: March 30, 2026, 6:09 p.m.