Triple

T13956991
Position Surface form Disambiguated ID Type / Status
Subject Puerto Escondido International Airport E335689 entity
Predicate ICAOcode P419 FINISHED
Object MMPS
MMPS is the ICAO airport code assigned to Puerto Escondido International Airport in Oaxaca, Mexico.
 E1071611 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: MMPS | Statement: [Puerto Escondido International Airport, ICAOcode, MMPS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MMPS
Context triple: [Puerto Escondido International Airport, ICAOcode, MMPS]
  • A. MMP
    MMP is a hybrid electoral system that combines single-member district representation with proportional party lists to align a legislature’s overall seat distribution with parties’ share of the vote.
  • B. MMPB
    MMPB is the ICAO airport code for Puebla International Airport, a commercial airport serving the city of Puebla in central Mexico.
  • C. MMCP
    MMCP is the ICAO airport code for Ing. Alberto Acuña Ongay International Airport in Campeche, Mexico.
  • D. MPS
    MPS is a leading German research institute specializing in the study of the Sun and the solar system, operating under the Max Planck Society.
  • E. MPS
    MPS (Metal Performance Shaders) is an Apple framework that provides highly optimized GPU-accelerated compute and graphics shaders for tasks like image processing and machine learning on Apple devices.
  • 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: MMPS
Triple: [Puerto Escondido International Airport, ICAOcode, MMPS]
Generated description
MMPS is the ICAO airport code assigned to Puerto Escondido International Airport in Oaxaca, Mexico.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MMPS
Target entity description: MMPS is the ICAO airport code assigned to Puerto Escondido International Airport in Oaxaca, Mexico.
  • A. MMP
    MMP is a hybrid electoral system that combines single-member district representation with proportional party lists to align a legislature’s overall seat distribution with parties’ share of the vote.
  • B. MMPB
    MMPB is the ICAO airport code for Puebla International Airport, a commercial airport serving the city of Puebla in central Mexico.
  • C. MMCP
    MMCP is the ICAO airport code for Ing. Alberto Acuña Ongay International Airport in Campeche, Mexico.
  • D. MPS
    MPS is a leading German research institute specializing in the study of the Sun and the solar system, operating under the Max Planck Society.
  • E. MPS
    MPS is a language workbench and integrated development environment by JetBrains designed for creating and working with domain-specific languages using projectional editing.
  • 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_69d81c61f3508190aaf2ca0dc0002c59 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2e7a34f08190aa0d88b66154f268 completed April 14, 2026, 12:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69fba1d27a0c8190b5d95ea86fc1a420 completed May 6, 2026, 8:17 p.m.
NEDg Description generation batch_69fba6af4ed881908cb4b79cfa40977c completed May 6, 2026, 8:38 p.m.
NED2 Entity disambiguation (via description) batch_69fba71a91fc8190b24185994673b33b completed May 6, 2026, 8:39 p.m.
Created at: April 9, 2026, 10:17 p.m.