Triple

T16192553
Position Surface form Disambiguated ID Type / Status
Subject King Fahd Air Base E392977 entity
Predicate hasICAOCode P419 FINISHED
Object OETF
OETF is the ICAO airport code assigned to King Fahd Air Base in Saudi Arabia.
E631615 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: OETF | Statement: [King Fahd Air Base, hasICAOCode, OETF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: OETF
Context triple: [King Fahd Air Base, hasICAOCode, OETF]
  • A. OETF
    OETF is the ICAO airport code assigned to Taif Regional Airport in Taif, Saudi Arabia.
  • B. Rec. 709
    Rec. 709 is the ITU-R standard that defines the color space, transfer characteristics, and other parameters for HDTV video, widely used as the baseline for high-definition television and video production.
  • C. OEDF
    OEDF is the ICAO airport code assigned to King Fahd International Airport in Dammam, Saudi Arabia.
  • D. SMPTE ST 2084
    SMPTE ST 2084 is a high-dynamic-range (HDR) electro‑optical transfer function standard, also known as Perceptual Quantizer (PQ), widely used in modern HDR video systems such as HDR10 and Dolby Vision.
  • E. EBU color bars
    EBU color bars are a standardized television test pattern used primarily in Europe to calibrate and align video equipment according to European Broadcasting Union specifications.
  • 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: OETF
Triple: [King Fahd Air Base, hasICAOCode, OETF]
Generated description
OETF is the ICAO airport code assigned to King Fahd Air Base in Saudi Arabia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: OETF
Target entity description: OETF is the ICAO airport code assigned to King Fahd Air Base in Saudi Arabia.
  • A. OETF chosen
    OETF is the ICAO airport code assigned to Taif Regional Airport in Taif, Saudi Arabia.
  • B. Rec. 709
    Rec. 709 is the ITU-R standard that defines the color space, transfer characteristics, and other parameters for HDTV video, widely used as the baseline for high-definition television and video production.
  • C. OEDF
    OEDF is the ICAO airport code assigned to King Fahd International Airport in Dammam, Saudi Arabia.
  • D. SMPTE ST 2084
    SMPTE ST 2084 is a high-dynamic-range (HDR) electro‑optical transfer function standard, also known as Perceptual Quantizer (PQ), widely used in modern HDR video systems such as HDR10 and Dolby Vision.
  • E. EBU color bars
    EBU color bars are a standardized television test pattern used primarily in Europe to calibrate and align video equipment according to European Broadcasting Union specifications.
  • F. None of above.

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_69d87f1e49ac8190a311b54d32990576 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e222d6975c8190a512a65d5b0021bb completed April 17, 2026, 12:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffff0bfd08819083afc4bea1b99aad completed May 10, 2026, 3:44 a.m.
NEDg Description generation batch_6a0001b815c481908ed6fcaea42ee9fc completed May 10, 2026, 3:55 a.m.
NED2 Entity disambiguation (via description) batch_6a0002106a5c8190b92d27f01178a321 completed May 10, 2026, 3:57 a.m.
Created at: April 10, 2026, 5:02 a.m.