Triple

T1760214
Position Surface form Disambiguated ID Type / Status
Subject Newark E38639 entity
Predicate hasNeighborhood P40 FINISHED
Object Ironbound E127547 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: Ironbound | Statement: [Newark, hasNeighborhood, Ironbound]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ironbound
Context triple: [Newark, hasNeighborhood, Ironbound]
  • A. Ironbound chosen
    Ironbound is a vibrant, historically immigrant-rich neighborhood in Newark, New Jersey, known for its Portuguese, Brazilian, and Latin American culture, restaurants, and nightlife.
  • B. Cold Irons Bound
    "Cold Irons Bound" is a Grammy-winning, blues-infused song by Bob Dylan, noted for its dense, apocalyptic lyrics and murky, atmospheric production.
  • C. The Iron Mistress
    The Iron Mistress is a 1952 historical adventure film about the life of frontiersman Jim Bowie, noted for its swashbuckling action and romantic drama.
  • D. The Fire
    The Fire is a Major League Soccer club based in Chicago, Illinois, known formally as Chicago Fire FC.
  • E. The Green Rust
    The Green Rust is a 1919 crime thriller novel by Edgar Wallace involving a sinister plot to destroy the world’s wheat supply.
  • 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_69a8862d562481908d7025a1c1f67c0d completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa64410b58819098be7dc5da23d7af completed March 6, 2026, 5:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada0ec80f48190bcdc92e5ed4e44e6 completed March 8, 2026, 4:16 p.m.
Created at: March 4, 2026, 7:31 p.m.