Triple

T9369402
Position Surface form Disambiguated ID Type / Status
Subject Operation Thunderbolt E225489 entity
Predicate aircraftDestination P16154 FINISHED
Object Paris E568 NE FINISHED

How this triple was built (3 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: Paris | Statement: [Operation Thunderbolt, aircraftDestination, Paris]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paris
Context triple: [Operation Thunderbolt, aircraftDestination, Paris]
  • A. Paris chosen
    Paris is the capital and largest city of France, renowned for its historic architecture, art, fashion, and cultural influence worldwide.
  • B. Paris
    Paris is a prince of Troy in Greek mythology, best known for judging the beauty contest of the goddesses and for abducting Helen, which sparked the Trojan War.
  • C. Paris
    Paris is a major Chilean department store and retail chain offering a wide range of apparel, home goods, and consumer products.
  • D. Paris
    Paris is a budget-oriented AMD Sempron processor core designed for entry-level desktop computing.
  • E. Parigi
    Parigi is a coastal town that serves as the administrative center of Parigi Moutong Regency in Central Sulawesi, Indonesia.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: aircraftDestination
Context triple: [Operation Thunderbolt, aircraftDestination, Paris]
  • A. destinationOfFlight chosen
    Indicates the location or place to which a given flight is traveling or scheduled to arrive.
  • B. typicalDestinationAirportIATA
    Indicates the IATA airport code that is typically the destination in this kind of trip or route.
  • C. lastFlightPlannedLandingSite
    Indicates the location where the most recent flight is scheduled to land.
  • D. embarkedAircraft
    Indicates that one entity boarded or got onto an aircraft as a passenger or occupant.
  • E. journeyDestination
    Indicates that one entity serves as the endpoint or intended destination of another entity’s journey or travel.
  • F. None of above.

Provenance (4 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_69ca842cbddc819099d71ecec48cf9e5 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd5080f55c8190bd5ca0dc0a4ea989 completed April 1, 2026, 5:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0f3c197208190bde7850de266fdf0 completed April 4, 2026, 11:19 a.m.
PD Predicate disambiguation batch_69cc7a6abb8c81908c7a2f4ee92cc949 completed April 1, 2026, 1:52 a.m.
Created at: March 30, 2026, 7:43 p.m.