Triple

T15772349
Position Surface form Disambiguated ID Type / Status
Subject TBL1+ E382391 entity
Predicate hasComponent P35 FINISHED
Object Eurobalise E788602 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: Eurobalise | Statement: [TBL1+, hasComponent, Eurobalise]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eurobalise
Context triple: [TBL1+, hasComponent, Eurobalise]
  • A. Eurobalise chosen
    Eurobalise is a track-mounted transponder used in European railway signaling to transmit data to passing trains for control and safety purposes.
  • B. Eurosam
    Eurosam is a European defense consortium specializing in the design and production of advanced surface-to-air missile systems.
  • C. Europa Reach
    Europa Reach is a specific waterway or passage within the Douglas Channel system, likely serving as one of its navigable reaches along the British Columbia coast.
  • D. Eurosat
    Eurosat is an indoor steel roller coaster at Europa-Park in Germany, themed around space travel and known for its distinctive geodesic dome structure.
  • E. EGNOS
    EGNOS is a European satellite-based augmentation system that improves the accuracy and reliability of GPS signals for aviation and other safety-critical applications.
  • 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_69d86da09a10819082fe9797b23e4664 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e051976d248190adddd3db9f758e22 completed April 16, 2026, 3:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff877c5ae88190aeb500bb5f0d73f7 completed May 9, 2026, 7:14 p.m.
Created at: April 10, 2026, 4:47 a.m.