Triple

T7655422
Position Surface form Disambiguated ID Type / Status
Subject Jerez Airport E173367 entity
Predicate IATAcode P418 FINISHED
Object XRY
XRY is the IATA airport code for Jerez Airport, an international airport serving Jerez de la Frontera and the surrounding Cádiz region in southern Spain.
 E680145 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: XRY | Statement: [Jerez Airport, IATAcode, XRY]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: XRY
Context triple: [Jerez Airport, IATAcode, XRY]
  • A. XRX
    XRX is the stock ticker symbol for Xerox Holdings Corporation, an American company known for its document management technologies and printing solutions.
  • B. XU
    XU was a clandestine Norwegian intelligence organization that gathered and transmitted vital information to the Allies during the German occupation in World War II.
  • C. YXU
    YXU is the IATA airport code for London International Airport serving London, Ontario, Canada.
  • D. Xing
    Xing is a German-based professional networking platform focused on career development and business connections, particularly in German-speaking countries.
  • E. XiRonga
    XiRonga is a Bantu language spoken primarily by the Ronga people in southern Mozambique and surrounding regions.
  • 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: XRY
Triple: [Jerez Airport, IATAcode, XRY]
Generated description
XRY is the IATA airport code for Jerez Airport, an international airport serving Jerez de la Frontera and the surrounding Cádiz region in southern Spain.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: XRY
Target entity description: XRY is the IATA airport code for Jerez Airport, an international airport serving Jerez de la Frontera and the surrounding Cádiz region in southern Spain.
  • A. XRX
    XRX is the stock ticker symbol for Xerox Holdings Corporation, an American company known for its document management technologies and printing solutions.
  • B. XU
    XU was a clandestine Norwegian intelligence organization that gathered and transmitted vital information to the Allies during the German occupation in World War II.
  • C. YXU
    YXU is the IATA airport code for London International Airport serving London, Ontario, Canada.
  • D. Xing
    Xing is a German-based professional networking platform focused on career development and business connections, particularly in German-speaking countries.
  • E. XiRonga
    XiRonga is a Bantu language spoken primarily by the Ronga people in southern Mozambique and surrounding regions.
  • 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_69c6995473348190a4f41d110d619a18 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7018ea3688190907c3ac7d25e3da6 completed March 27, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c89afd1438819080c8f097df1d1453 completed March 29, 2026, 3:22 a.m.
NEDg Description generation batch_69c89ec399708190bce316010799298e completed March 29, 2026, 3:38 a.m.
NED2 Entity disambiguation (via description) batch_69c89f23221c81909efe8596333b7f1c completed March 29, 2026, 3:40 a.m.
Created at: March 27, 2026, 3:59 p.m.