Triple

T8690331
Position Surface form Disambiguated ID Type / Status
Subject Miranda Kerr E206269 entity
Predicate modeledFor P2006 FINISHED
Object Mango E4043 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: Mango | Statement: [Miranda Kerr, modeledFor, Mango]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mango
Context triple: [Miranda Kerr, modeledFor, Mango]
  • A. Mango chosen
    Mango is a sweet, tropical stone fruit widely cultivated and consumed around the world, especially in South Asia.
  • B. Haden mango
    Haden mango is a historically important and widely grown mango cultivar from Florida known for its rich flavor, vibrant color, and role as a parent to many modern mango varieties.
  • C. Mulgoba mango
    Mulgoba mango is a classic Indian mango cultivar known for its rich flavor and aromatic, fiberless flesh, and for serving as a parent to several important modern mango varieties.
  • D. Litchi
    Litchi is a tropical fruit-bearing tree genus best known for producing sweet, aromatic lychee fruits with rough red skins and translucent white flesh.
  • E. Keitt mango
    Keitt mango is a late-season, large, green-skinned mango cultivar prized for its sweet, fiberless flesh and extended shelf life.
  • 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_69ca835481fc819084e33d3bc883bfa6 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5734602c81909a0687e00f4a4a26 completed March 31, 2026, 11:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69cef3df73b88190b67138ee5129de8b completed April 2, 2026, 10:55 p.m.
Created at: March 30, 2026, 6:33 p.m.