Triple

T3874108
Position Surface form Disambiguated ID Type / Status
Subject Salalah Airport E92455 entity
Predicate ICAOcode P419 FINISHED
Object OOSA
OOSA is the ICAO airport code for Salalah Airport, an international airport serving the city of Salalah in Oman.
E395528 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: OOSA | Statement: [Salalah Airport, ICAOcode, OOSA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: OOSA
Context triple: [Salalah Airport, ICAOcode, OOSA]
  • A. OASAM
    OASAM is a division of the U.S. Department of Labor responsible for providing administrative, management, and support services across the department.
  • B. OSO
    OSO is the commonly used abbreviation for the Office of SIGINT Operations, a signals intelligence unit within the U.S. National Security Agency.
  • C. OASAS
    OASAS is the New York State agency responsible for overseeing and supporting addiction prevention, treatment, and recovery services.
  • D. OSS Society
    The OSS Society is a nonprofit organization dedicated to honoring the legacy and preserving the history of the World War II-era Office of Strategic Services and its role in U.S. intelligence and special operations.
  • E. OCS
    OCS is a United States Marine Corps training program that evaluates and prepares prospective officers for commissioning.
  • 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: OOSA
Triple: [Salalah Airport, ICAOcode, OOSA]
Generated description
OOSA is the ICAO airport code for Salalah Airport, an international airport serving the city of Salalah in Oman.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: OOSA
Target entity description: OOSA is the ICAO airport code for Salalah Airport, an international airport serving the city of Salalah in Oman.
  • A. OASAM
    OASAM is a division of the U.S. Department of Labor responsible for providing administrative, management, and support services across the department.
  • B. OSO
    OSO is the commonly used abbreviation for the Office of SIGINT Operations, a signals intelligence unit within the U.S. National Security Agency.
  • C. OASAS
    OASAS is the New York State agency responsible for overseeing and supporting addiction prevention, treatment, and recovery services.
  • D. OSS Society
    The OSS Society is a nonprofit organization dedicated to honoring the legacy and preserving the history of the World War II-era Office of Strategic Services and its role in U.S. intelligence and special operations.
  • E. OCS
    OCS is a United States Marine Corps training program that evaluates and prepares prospective officers for commissioning.
  • 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_69aed967448c819086c4b358d37b25aa completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeec59bea08190b1e193f34944a2ee completed March 9, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5124cdf588190b3b83ee8fb29450a completed March 14, 2026, 7:46 a.m.
NEDg Description generation batch_69b5132715888190bc5ba6182965e813 completed March 14, 2026, 7:49 a.m.
NED2 Entity disambiguation (via description) batch_69b513b11dcc8190a2c2e3f27b4cf25e completed March 14, 2026, 7:52 a.m.
Created at: March 9, 2026, 3:20 p.m.