Triple

T2230005
Position Surface form Disambiguated ID Type / Status
Subject EgyptAir E48742 entity
Predicate IATACode P418 FINISHED
Object MS
MS is the two-letter IATA airline designator assigned to EgyptAir, the flag carrier of Egypt.
 E245443 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: MS | Statement: [EgyptAir, IATACode, MS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MS
Context triple: [EgyptAir, IATACode, MS]
  • A. MS
    MS is a postgraduate Master of Science degree typically focused on advanced study and research in scientific or technical disciplines.
  • B. MS
    MS is the two-letter ISO 3166 country code assigned to the British Overseas Territory of Montserrat in the Caribbean.
  • C. MS
    MS is the official two-letter United States Postal Service abbreviation for the state of Mississippi.
  • D. MS
    MS is the official vehicle registration code used on license plates for the German city of Münster.
  • E. MSA
    MSA is the common abbreviation for the Master Settlement Agreement, a landmark 1998 legal settlement between major U.S. tobacco companies and state attorneys general that reshaped tobacco advertising and funded public health initiatives.
  • 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: MS
Triple: [EgyptAir, IATACode, MS]
Generated description
MS is the two-letter IATA airline designator assigned to EgyptAir, the flag carrier of Egypt.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MS
Target entity description: MS is the two-letter IATA airline designator assigned to EgyptAir, the flag carrier of Egypt.
  • A. MS
    MS is the official two-letter United States Postal Service abbreviation for the state of Mississippi.
  • B. MS
    MS is the two-letter ISO 3166 country code assigned to the British Overseas Territory of Montserrat in the Caribbean.
  • C. MS
    MS is the official vehicle registration code used on license plates for the German city of Münster.
  • D. MS
    MS is a postgraduate Master of Science degree typically focused on advanced study and research in scientific or technical disciplines.
  • E. MSA
    MSA is the common abbreviation for the Master Settlement Agreement, a landmark 1998 legal settlement between major U.S. tobacco companies and state attorneys general that reshaped tobacco advertising and funded public health initiatives.
  • 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_69a88aa51b388190949868ec9766e587 completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc069e0ac8190bcda8cba9f5c7a5d completed March 7, 2026, 6:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae656a1f788190a08c3283bfedb6f4 completed March 9, 2026, 6:15 a.m.
NEDg Description generation batch_69ae65d4f26481909808c97b95ca9b30 completed March 9, 2026, 6:16 a.m.
NED2 Entity disambiguation (via description) batch_69ae6670b6d88190a09023fae63f4000 completed March 9, 2026, 6:19 a.m.
Created at: March 4, 2026, 7:47 p.m.