Triple

T34998007
Position Surface form Disambiguated ID Type / Status
Subject Porto metropolitan public transport network E1009591 entity
Predicate airportConnectionMode P33519 FINISHED
Object metro Line E
Metro Line E is a light rail line in Porto’s metro system that provides direct service between the city and Francisco Sá Carneiro Airport.
 E2120258 NE FINISHED

How this triple was built (3 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: metro Line E | Statement: [Porto metropolitan public transport network, airportConnectionMode, metro Line E]
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: metro Line E
Triple: [Porto metropolitan public transport network, airportConnectionMode, metro Line E]
Generated description
Metro Line E is a light rail line in Porto’s metro system that provides direct service between the city and Francisco Sá Carneiro Airport.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: airportConnectionMode
Context triple: [Porto metropolitan public transport network, airportConnectionMode, metro Line E]
  • A. airportAccessMode chosen
    Indicates the typical mode or method of transportation used to access or reach an airport.
  • B. connectsWithAirport
    Indicates that there is a direct transportation or operational link established between an entity and an airport.
  • C. hasAirsideConnection
    Indicates that there is a direct, secure connection between areas past security (airside) of two locations, allowing passengers to transfer without re-clearing security or immigration.
  • D. airportTypeManaged
    Indicates that an entity is responsible for managing or overseeing a particular type or category of airport.
  • E. airportTypePresent
    Indicates that a specific type or category of airport is present or exists in relation to the referenced entity.
  • F. None of above.

Provenance (6 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_69f76dca50dc8190b71f39defe186be8 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78710282c81909146dc0be91e983f completed May 3, 2026, 5:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37b28fc3fc8190a897949f7f673539 completed June 21, 2026, 9:44 a.m.
NEDg Description generation batch_6a37b38d3bc4819094bf270b456b80b1 completed June 21, 2026, 9:49 a.m.
NED2 Entity disambiguation (via description) batch_6a37b47166f48190a351377c2080628e completed June 21, 2026, 9:52 a.m.
PD Predicate disambiguation batch_69f784162134819098413482ef52042f completed May 3, 2026, 5:21 p.m.
Created at: May 3, 2026, 4:01 p.m.