Triple

T3267569
Position Surface form Disambiguated ID Type / Status
Subject Chicago community areas E68562 entity
Predicate includeExample P1259 FINISHED
Object Loop E17325 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: Loop | Statement: [Chicago community areas, includeExample, Loop]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Loop
Context triple: [Chicago community areas, includeExample, Loop]
  • A. Loop chosen
    The Loop is Chicago’s central business district and downtown core, known for its dense cluster of skyscrapers, cultural institutions, and historic elevated train system.
  • B. Loop
    Loop is a Microsoft 365 collaborative workspace app that lets teams create, share, and co-edit dynamic content blocks in real time across Microsoft’s productivity tools.
  • C. Looper
    Looper is a 2012 science-fiction action film directed by Rian Johnson, known for its time-travel premise and starring Joseph Gordon-Levitt and Bruce Willis.
  • D. A Loop
    A Loop is a modern streetcar route in Portland, Oregon, that provides circulator service through the central city and adjacent neighborhoods as part of the Portland Streetcar system.
  • E. Loopt
    Loopt was an early location-based social networking mobile app startup that allowed users to share their real-time location with friends.
  • 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_69ad8590444081909e8107a8aeef3a23 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adafcf9c6c819092f9c618b778b46d completed March 8, 2026, 5:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69b28ef261ec819091c62620765e2cef completed March 12, 2026, 10:01 a.m.
Created at: March 8, 2026, 3:09 p.m.