Triple

T1070321
Position Surface form Disambiguated ID Type / Status
Subject Erzhausen E23310 entity
Predicate locatedNearTransportHub P2413 FINISHED
Object Frankfurt Airport E95589 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: Frankfurt Airport | Statement: [Erzhausen, locatedNearTransportHub, Frankfurt Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frankfurt Airport
Context triple: [Erzhausen, locatedNearTransportHub, Frankfurt Airport]
  • A. Frankfurt Airport chosen
    Frankfurt Airport is one of Europe’s busiest international aviation hubs, serving as a major global gateway and primary airport for the city of Frankfurt am Main in Germany.
  • B. Hamburg Airport
    Hamburg Airport is an international airport in northern Germany serving the city of Hamburg and the surrounding region as a major passenger and cargo hub.
  • C. Munich Airport
    Munich Airport is a major international aviation hub in Bavaria, Germany, serving as one of the country’s busiest airports and a key base for Lufthansa.
  • D. Nuremberg Airport
    Nuremberg Airport is an international airport in northern Bavaria, Germany, serving the city of Nuremberg and the surrounding Franconia region with passenger and cargo flights.
  • E. Hannover Airport
    Hannover Airport is an international airport serving the city of Hanover in northern Germany, handling passenger and cargo flights for the region.
  • 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: locatedNearTransportHub
Context triple: [Erzhausen, locatedNearTransportHub, Frankfurt Airport]
  • A. hasPublicTransportStop
    Indicates that a location or area contains or is served by a public transport stop, such as a bus, tram, or train stop.
  • B. hasPublicTransportConnection
    Indicates that there is an available public transportation link or service connecting the related entities.
  • C. hasTransportHub chosen
    Indicates that a location contains or serves as a central facility where multiple transport routes or modes connect for passenger or cargo movement.
  • D. hasBusStation
    Indicates that a place or area contains or is served by a bus station.
  • E. nearestPassengerRailStation
    Indicates that one entity is the closest passenger rail station in distance to another entity.
  • 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_69a493ee1f908190992b5f0d1b04459b completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b914b4908190886d6698294c6b5b completed March 1, 2026, 10:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac4c1fb7948190b08c95e68d3de00e completed March 7, 2026, 4:02 p.m.
PD Predicate disambiguation batch_69a4b73844708190a16c9e9824ca2fb6 completed March 1, 2026, 10:01 p.m.
Created at: March 1, 2026, 7:42 p.m.