Triple

T2449923
Position Surface form Disambiguated ID Type / Status
Subject University of the Philippines E53677 entity
Predicate abbreviation P43 FINISHED
Object UP E187970 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: UP | Statement: [University of the Philippines, abbreviation, UP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: UP
Context triple: [University of the Philippines, abbreviation, UP]
  • A. UP
    UP is the standard reporting mark used to identify rail equipment owned or operated by the Union Pacific Railroad in North America.
  • B. UP chosen
    UP is a leading South African public research university located in Pretoria, known for its comprehensive range of academic programs and strong research output.
  • C. Up
    Up is a critically acclaimed 2009 Pixar animated film that follows an elderly widower and a young boy on a fantastical balloon-lifted house adventure, noted for its emotional depth and imaginative storytelling.
  • D. UP-W
    UP-W is the service designation used by Metra for its Union Pacific West commuter rail line in the Chicago metropolitan area.
  • E. UPP
    UPP is a reporting mark used by the Union Pacific Railroad to identify certain passenger cars and related rolling stock in its fleet.
  • 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_69ab495d227c8190b26ae6548eeb1019 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd0f2b8488190b1f6a86f0a9f83aa completed March 7, 2026, 7:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69af17907f48819092f197ba14459b17 completed March 9, 2026, 6:55 p.m.
Created at: March 6, 2026, 9:43 p.m.