Triple

T14920301
Position Surface form Disambiguated ID Type / Status
Subject Maseeh College of Engineering and Computer Science E371491 entity
Predicate city P40 FINISHED
Object Portland E182044 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: Portland | Statement: [Maseeh College of Engineering and Computer Science, city, Portland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Portland
Context triple: [Maseeh College of Engineering and Computer Science, city, Portland]
  • A. Portland
    Portland is a small historic town in the Central Tablelands region of New South Wales, Australia, known for its early cement works and heritage streetscapes.
  • B. Portland chosen
    Portland is the largest city in Oregon, known for its vibrant arts scene, progressive culture, and lush green spaces in the Pacific Northwest.
  • C. Portland
    Portland is the largest city in the U.S. state of Maine, known for its historic waterfront, vibrant arts scene, and coastal New England charm.
  • D. Portland
    Portland is a tied island and civil parish on the Jurassic Coast in Dorset, England, known for its historic quarries, lighthouse, and role as a former naval base.
  • E. Portlands
    Portlands is a residential suburb within Mitchells Plain, a large township on the Cape Flats in Cape Town, South Africa.
  • 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_69d85cc7ea3481908228b5acb7d06f12 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded62f76bc81909ebc8899096cd1a0 completed April 15, 2026, 12:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69fea59d27bc81908ace0b7db9f57215 completed May 9, 2026, 3:10 a.m.
Created at: April 10, 2026, 2:33 a.m.