Triple

T8832166
Position Surface form Disambiguated ID Type / Status
Subject Penning trap E210170 entity
Predicate relatedConcept P37 FINISHED
Object Paul trap E608818 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: Paul trap | Statement: [Penning trap, relatedConcept, Paul trap]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paul trap
Context triple: [Penning trap, relatedConcept, Paul trap]
  • A. Paul trap chosen
    The Paul trap is a type of ion trap that uses oscillating electric fields to confine charged particles, widely used in precision spectroscopy, mass spectrometry, and quantum computing experiments.
  • B. Paul Carnal
    Paul Carnal was the Swiss educator who established Institut Le Rosey, one of the world’s most prestigious and exclusive boarding schools.
  • C. Paulus Potter
    Paulus Potter was a renowned 17th-century Dutch Golden Age painter celebrated for his detailed and lifelike depictions of animals and rural landscapes.
  • D. Philip Sabes
    Philip Sabes is a neuroscientist and entrepreneur known for his work on brain–computer interfaces and for co-founding the neurotechnology company Neuralink.
  • E. Daniel Auster
    Daniel Auster was a prominent Zionist politician and lawyer who served as mayor of Jerusalem during the British Mandate period.
  • 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_69ca8365b28081909e48e45e95dfc405 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc605005788190a4df1fe317f3056a completed April 1, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69cf896cf5a8819098a76288bd505c1e completed April 3, 2026, 9:33 a.m.
Created at: March 30, 2026, 6:47 p.m.