Triple

T3414997
Position Surface form Disambiguated ID Type / Status
Subject Scala E71988 entity
Predicate developer P73 FINISHED
Object EPFL E24200 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: EPFL | Statement: [Scala, developer, EPFL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: EPFL
Context triple: [Scala, developer, EPFL]
  • A. École polytechnique fédérale de Lausanne chosen
    École polytechnique fédérale de Lausanne is a leading Swiss research university and engineering school known for its cutting-edge work in science, technology, and innovation.
  • B. École polytechnique fédérale de Zurich
    École polytechnique fédérale de Zurich is a leading Swiss public research university in Zurich renowned worldwide for its excellence in science, engineering, and technology.
  • C. University of Lausanne
    The University of Lausanne is a major public research university in Lausanne, Switzerland, known for its strengths in law, business, life sciences, and social sciences.
  • D. ETH Zurich
    ETH Zurich is a leading Swiss public research university in Zurich renowned for its excellence in science, engineering, and technology education and innovation.
  • E. ENS Paris-Saclay
    ENS Paris-Saclay is a prestigious French grande école that trains high-level researchers, academics, and professionals in science and humanities within the Université Paris-Saclay system.
  • 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_69ad85ac312481909e7027ced1456a9f completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb929b8ec8190aef431ec8ea2cf80 completed March 8, 2026, 6 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4881f1e1c81908de3a0729761c4f7 completed March 13, 2026, 9:56 p.m.
Created at: March 8, 2026, 3:15 p.m.