Triple

T304358
Position Surface form Disambiguated ID Type / Status
Subject Haarlemmermeer E6265 entity
Predicate contains P35 FINISHED
Object Amsterdam Airport Schiphol E15161 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: Amsterdam Airport Schiphol | Statement: [Haarlemmermeer, contains, Amsterdam Airport Schiphol]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amsterdam Airport Schiphol
Context triple: [Haarlemmermeer, contains, Amsterdam Airport Schiphol]
  • A. Amsterdam Airport Schiphol chosen
    Amsterdam Airport Schiphol is the main international airport of the Netherlands and one of Europe’s busiest aviation hubs for passenger and cargo traffic.
  • B. Brussels Airport
    Brussels Airport is the main international airport serving Brussels and one of Belgium’s busiest air transport hubs for passengers and cargo.
  • C. Brussels South Charleroi Airport
    Brussels South Charleroi Airport is a major low-cost international airport in Belgium, widely used by budget airlines and serving as an alternative to Brussels Airport.
  • D. Rotterdam
    Rotterdam is a major Dutch port city known for having one of the world’s largest harbors and striking modern architecture.
  • E. Amsterdam Centraal
    Amsterdam Centraal is the main railway hub of Amsterdam and one of the busiest train stations in the Netherlands, serving as a central gateway for national and international rail travel.
  • 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_69a2e79230508190b912ecb555aae17e completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2ea1032e48190864338e030d9dc92 completed Feb. 28, 2026, 1:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3b07566c88190af82b1953902b613 completed March 1, 2026, 3:20 a.m.
Created at: Feb. 28, 2026, 1:06 p.m.