Triple

T5199405
Position Surface form Disambiguated ID Type / Status
Subject Avril Lavigne E117354 entity
Predicate album P1995 FINISHED
Object Head Above Water E500520 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: Head Above Water | Statement: [Avril Lavigne, album, Head Above Water]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Head Above Water
Context triple: [Avril Lavigne, album, Head Above Water]
  • A. Head Above Water chosen
    "Head Above Water" is a 2018 pop-rock ballad by Canadian singer Avril Lavigne that marked her comeback after a long battle with Lyme disease.
  • B. Deep Water
    "Deep Water" is a soulful, introspective song by British singer Seal from his self-titled debut album, blending atmospheric production with emotive vocals.
  • C. Don’t Go Near the Water
    Don’t Go Near the Water is a 1957 American romantic comedy film set in the U.S. Navy during World War II, known for its humorous take on military public relations and wartime romance.
  • D. Spirit on the Water
    "Spirit on the Water" is a reflective, blues-inflected song by Bob Dylan from his 2006 album *Modern Times*, noted for its laid-back groove and lyrical blend of romance, humor, and spiritual allusion.
  • E. Blue Water
    Blue Water is an Amtrak passenger rail service operating in the Midwest, primarily connecting Chicago with cities in Michigan.
  • 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_69bd4462ed04819084fcb01eb9d2fa74 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7a209d7c81908fa0d3bf2c482a34 completed March 20, 2026, 4:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69beefc60abc8190a0abcaf8b42dfe3d completed March 21, 2026, 7:21 p.m.
Created at: March 20, 2026, 1:47 p.m.