Triple

T16061583
Position Surface form Disambiguated ID Type / Status
Subject SkyTeam E389626 entity
Predicate hasMember P10 FINISHED
Object TAROM E32510 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: TAROM | Statement: [SkyTeam, hasMember, TAROM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TAROM
Context triple: [SkyTeam, hasMember, TAROM]
  • A. TAROM chosen
    TAROM is the national flag carrier airline of Romania, operating domestic and international flights primarily from its hub in Bucharest.
  • B. Turkish Airlines
    Turkish Airlines is the national flag carrier airline of Turkey, operating an extensive global network of passenger and cargo flights across Europe, Asia, Africa, and the Americas.
  • C. Hunnu Air
    Hunnu Air is a Mongolian airline that operates domestic and regional international flights, primarily serving as a key carrier based in Ulaanbaatar.
  • D. Pegasus Airlines
    Pegasus Airlines is a Turkish low-cost carrier based in Istanbul that operates an extensive network of domestic and international flights across Europe, the Middle East, and beyond.
  • E. Bulgaria Air
    Bulgaria Air is the national flag carrier airline of Bulgaria, operating domestic and international flights across Europe and the Middle East.
  • 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_69d86dae698881908327ef2d67706cb9 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e183795100819097be92e6d07dc5b1 completed April 17, 2026, 12:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffdbe88a608190bc0a0cbfdb71e81d completed May 10, 2026, 1:14 a.m.
Created at: April 10, 2026, 4:57 a.m.