Triple

T3530039
Position Surface form Disambiguated ID Type / Status
Subject Damrak E74635 entity
Predicate hasNearbyWater P49291 FINISHED
Object IJ E159017 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: IJ | Statement: [Damrak, hasNearbyWater, IJ]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: IJ
Context triple: [Damrak, hasNearbyWater, IJ]
  • A. IJ chosen
    The IJ is a body of water in Amsterdam that serves as a key waterway for transport and shipping, separating the city center from Amsterdam-Noord.
  • B. J
    J is a New York City Subway service that runs through Brooklyn and Queens into Manhattan, serving neighborhoods in eastern Brooklyn and southern Queens.
  • C. J
    J is one of the passenger concourses at Miami International Airport, serving as a terminal area with gates, amenities, and airline operations for departing and arriving flights.
  • D. JO
    JO is the two-letter ISO 3166-1 alpha-2 country code assigned to the Hashemite Kingdom of Jordan.
  • E. IER
    IER is a division of the U.S. Department of Justice that enforces federal laws protecting immigrants and other workers from employment discrimination based on citizenship or immigration status and national origin.
  • 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_69ad85d1a3948190931fd1ea1f49717b completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc9764a881908aa8d25dc9adf59e completed March 8, 2026, 6:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69b37e97536881908d5ed3dfe602c9e0 completed March 13, 2026, 3:03 a.m.
Created at: March 8, 2026, 3:19 p.m.