Triple

T12007209
Position Surface form Disambiguated ID Type / Status
Subject Série 4000 E285810 entity
Predicate primaryRoute P6298 FINISHED
Object Porto–Faro
Porto–Faro is a major long-distance rail route in Portugal linking the northern city of Porto with the southern Algarve city of Faro.
 E984947 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: Porto–Faro | Statement: [Série 4000, primaryRoute, Porto–Faro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Porto–Faro
Context triple: [Série 4000, primaryRoute, Porto–Faro]
  • A. Lisbon–Faro
    Lisbon–Faro is a major intercity rail corridor in Portugal linking the capital Lisbon with the southern coastal city of Faro in the Algarve region.
  • B. Lisbon–Guimarães
    Lisbon–Guimarães is a major intercity rail route in Portugal connecting the capital Lisbon with the historic northern city of Guimarães.
  • C. Lisbon–Porto
    Lisbon–Porto is the main intercity rail corridor in Portugal, linking the capital Lisbon with the northern city of Porto.
  • D. Beira-Mar
    Beira-Mar is a Portuguese football club based in Aveiro, known for competing in the country’s professional leagues and developing notable players such as Eusébio.
  • E. Porto de Mós
    Porto de Mós is a Portuguese town and municipality known for its hilltop castle and location near the limestone landscapes and caves of central Portugal.
  • 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: Porto–Faro
Triple: [Série 4000, primaryRoute, Porto–Faro]
Generated description
Porto–Faro is a major long-distance rail route in Portugal linking the northern city of Porto with the southern Algarve city of Faro.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Porto–Faro
Target entity description: Porto–Faro is a major long-distance rail route in Portugal linking the northern city of Porto with the southern Algarve city of Faro.
  • A. Lisbon–Faro
    Lisbon–Faro is a major intercity rail corridor in Portugal linking the capital Lisbon with the southern coastal city of Faro in the Algarve region.
  • B. Lisbon–Guimarães
    Lisbon–Guimarães is a major intercity rail route in Portugal connecting the capital Lisbon with the historic northern city of Guimarães.
  • C. Lisbon–Porto
    Lisbon–Porto is the main intercity rail corridor in Portugal, linking the capital Lisbon with the northern city of Porto.
  • D. Beira-Mar
    Beira-Mar is a Portuguese football club based in Aveiro, known for competing in the country’s professional leagues and developing notable players such as Eusébio.
  • E. Porto de Mós
    Porto de Mós is a Portuguese town and municipality known for its hilltop castle and location near the limestone landscapes and caves of central Portugal.
  • 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_69d6ab45a368819084fce08bf0dc3705 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903c5cfc08190821e4b2940c51416 completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63edddad48190b5b4da184fde27dd completed May 2, 2026, 6:13 p.m.
NEDg Description generation batch_69f6415f11d88190a9f77eb1890f76ef completed May 2, 2026, 6:24 p.m.
NED2 Entity disambiguation (via description) batch_69f64231606481909b8dd9d878670a6c completed May 2, 2026, 6:28 p.m.
Created at: April 8, 2026, 9:46 p.m.