Triple

T8991130
Position Surface form Disambiguated ID Type / Status
Subject Flyadeal E214790 entity
Predicate callsign P1565 FINISHED
Object DOKOM
DOKOM is the radio callsign used by Flyadeal, a Saudi low-cost airline based in Jeddah.
 E770533 NE FINISHED

How this triple was built (4 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: DOKOM | Statement: [Flyadeal, callsign, DOKOM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DOKOM
Context triple: [Flyadeal, callsign, DOKOM]
  • A. Dok
    Dok is an ancient location associated with the Hasmonean leader Simon Thassi, known primarily as the site of his assassination.
  • B. Dokki
    Dokki is a prominent district in Giza, Egypt, known for its government institutions, educational centers, and residential neighborhoods just across the Nile from central Cairo.
  • C. Dokos
    Dokos is a small, sparsely inhabited Greek island in the Saronic Gulf, known for its rugged landscape and archaeological significance.
  • D. Dokk1
    Dokk1 is a large modern public library and cultural center on Aarhus’s waterfront, known as one of the city’s key architectural and civic landmarks.
  • E. DOCO
    DOCO is a mixed-use entertainment, shopping, and dining district in downtown Sacramento, California, adjacent to the Golden 1 Center.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: DOKOM
Triple: [Flyadeal, callsign, DOKOM]
Generated description
DOKOM is the radio callsign used by Flyadeal, a Saudi low-cost airline based in Jeddah.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: DOKOM
Target entity description: DOKOM is the radio callsign used by Flyadeal, a Saudi low-cost airline based in Jeddah.
  • A. Dok
    Dok is an ancient location associated with the Hasmonean leader Simon Thassi, known primarily as the site of his assassination.
  • B. Dokki
    Dokki is a prominent district in Giza, Egypt, known for its government institutions, educational centers, and residential neighborhoods just across the Nile from central Cairo.
  • C. Dokos
    Dokos is a small, sparsely inhabited Greek island in the Saronic Gulf, known for its rugged landscape and archaeological significance.
  • D. Dokk1
    Dokk1 is a large modern public library and cultural center on Aarhus’s waterfront, known as one of the city’s key architectural and civic landmarks.
  • E. DOCO
    DOCO is a mixed-use entertainment, shopping, and dining district in downtown Sacramento, California, adjacent to the Golden 1 Center.
  • F. None of above. chosen

Provenance (5 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_69ca83a05c608190bdfdbdb25e994b39 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc68753590819094fd70ed35d8cedf completed April 1, 2026, 12:36 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfd0c9659c8190ae7ff5df8e016d17 completed April 3, 2026, 2:38 p.m.
NEDg Description generation batch_69cfd16959f88190b153766133ffe0dc completed April 3, 2026, 2:40 p.m.
NED2 Entity disambiguation (via description) batch_69cfd1da79b8819096d753ea7836265c completed April 3, 2026, 2:42 p.m.
Created at: March 30, 2026, 7:04 p.m.