Triple

T3017311
Position Surface form Disambiguated ID Type / Status
Subject RAM E82367 entity
Predicate identifies P310 FINISHED
Object Royal Air Maroc E13189 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: Royal Air Maroc | Statement: [RAM, identifies, Royal Air Maroc]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Royal Air Maroc
Context triple: [RAM, identifies, Royal Air Maroc]
  • A. Royal Air Maroc chosen
    Royal Air Maroc is the flag carrier airline of Morocco, operating an extensive network of flights across Africa, Europe, the Americas, and the Middle East from its main hub in Casablanca.
  • B. Tunisair
    Tunisair is the flag carrier airline of Tunisia, operating domestic and international flights primarily from its hub in Tunis.
  • C. Gulf Air
    Gulf Air is the national flag carrier airline of the Kingdom of Bahrain, operating regional and international flights across the Middle East, Asia, Europe, and Africa.
  • D. Middle East Airlines
    Middle East Airlines is the national flag carrier of Lebanon, operating regional and international flights primarily from its hub at Beirut–Rafic Hariri International Airport.
  • E. Oman Air
    Oman Air is the national airline of Oman, operating regional and international flights from its main hub in Muscat.
  • 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_69ad8b1eb53481908c39bbcd1ec104b2 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9a90ea64819080620e60bbd6aa24 completed March 8, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b12e6eac1481909d56844e53c37b59 completed March 11, 2026, 8:57 a.m.
Created at: March 8, 2026, 3 p.m.