Triple

T11363964
Position Surface form Disambiguated ID Type / Status
Subject Porto Airport E269155 entity
Predicate IATAcode P418 FINISHED
Object OPO
OPO is the IATA airport code for Francisco Sá Carneiro Airport, the main international airport serving Porto, Portugal.
 E921502 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: OPO | Statement: [Porto Airport, IATAcode, OPO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: OPO
Context triple: [Porto Airport, IATAcode, OPO]
  • A. OPO
    OPO is the vehicle registration code assigned to the Polish city of Opole.
  • B. Opo
    The Opo are a small Nilotic ethnic group living primarily in the borderlands of western Ethiopia and South Sudan, known for their agro-pastoralist lifestyle and distinct language and culture.
  • C. OPOJAZ
    OPOJAZ was a pioneering Russian Formalist literary group in early 20th-century Petrograd that developed influential theories of literary form and technique.
  • D. OPA
    OPA is a U.S. federal law enacted in 1990 that strengthens regulations and liability standards for preventing and responding to oil spills in navigable waters and shorelines.
  • E. OPA
    OPA is a U.S. federal agency within the Department of Health and Human Services that oversees family planning, adolescent health, and related population affairs programs.
  • 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: OPO
Triple: [Porto Airport, IATAcode, OPO]
Generated description
OPO is the IATA airport code for Francisco Sá Carneiro Airport, the main international airport serving Porto, Portugal.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: OPO
Target entity description: OPO is the IATA airport code for Francisco Sá Carneiro Airport, the main international airport serving Porto, Portugal.
  • A. OPO
    OPO is the vehicle registration code assigned to the Polish city of Opole.
  • B. Opo
    The Opo are a small Nilotic ethnic group living primarily in the borderlands of western Ethiopia and South Sudan, known for their agro-pastoralist lifestyle and distinct language and culture.
  • C. OPOJAZ
    OPOJAZ was a pioneering Russian Formalist literary group in early 20th-century Petrograd that developed influential theories of literary form and technique.
  • D. OPA
    OPA is a U.S. federal law enacted in 1990 that strengthens regulations and liability standards for preventing and responding to oil spills in navigable waters and shorelines.
  • E. OPA
    OPA is a U.S. federal agency within the Department of Health and Human Services that oversees family planning, adolescent health, and related population affairs programs.
  • 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_69d6aacbe18081909e5fadb50082dd96 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7ea4589908190948a8225768e1eec completed April 9, 2026, 6:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5565df5508190aeda7d064bceb157 completed April 19, 2026, 10:25 p.m.
NEDg Description generation batch_69e562c6e7c8819098d22a6e0daa4a51 completed April 19, 2026, 11:18 p.m.
NED2 Entity disambiguation (via description) batch_69e56a472f0c819086c1cccaa5ca0ae7 completed April 19, 2026, 11:50 p.m.
Created at: April 8, 2026, 9:33 p.m.