Triple

T15241471
Position Surface form Disambiguated ID Type / Status
Subject Nicola Rescigno E364263 entity
Predicate residence P75 FINISHED
Object Dallas E669436 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: Dallas | Statement: [Nicola Rescigno, residence, Dallas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dallas
Context triple: [Nicola Rescigno, residence, Dallas]
  • A. Dallas
    Dallas is a small borough in northeastern Pennsylvania known as part of the suburban and educational hub of the Wyoming Valley near Wilkes-Barre.
  • B. Dallas chosen
    Dallas is a major city in north Texas known for its role as a commercial and cultural hub, particularly in the energy, telecommunications, and technology industries.
  • C. Dallas
    Dallas is a major city in northern Texas known for its role as a commercial and cultural hub, with a prominent skyline, diverse population, and significant influence in business, arts, and sports.
  • D. Dallas
    Dallas is a major city in northern Texas known for its role as a commercial and cultural hub, particularly in finance, technology, and the energy industry.
  • E. Dallas
    Dallas is a character appearing in the "Home Invasion" storyline.
  • 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_69d85a0dde7481908fc64d1e82d5d20d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e007dcc33081908545ea1a1d2c19fe completed April 15, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fef88bc8088190a357657c461f761d completed May 9, 2026, 9:04 a.m.
Created at: April 10, 2026, 3:13 a.m.