Triple

T15551453
Position Surface form Disambiguated ID Type / Status
Subject Budapest tram network E370752 entity
Predicate hasStop P17789 FINISHED
Object Margit híd stop
Margit híd stop is a tram station in Budapest located near the Margaret Bridge, serving as a key interchange point on the city's tram network.
 E1163586 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: Margit híd stop | Statement: [Budapest tram network, hasStop, Margit híd stop]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Margit híd stop
Context triple: [Budapest tram network, hasStop, Margit híd stop]
  • A. Dunántúl
    Dunántúl is the Hungarian name for Transdanubia, the large western region of Hungary lying west of the Danube River.
  • B. Maughold
    Maughold is a coastal parish and village on the Isle of Man known for its rugged cliffs, scenic coastline, and historic church with ancient Celtic crosses.
  • C. Fárrago
    Fárrago is a celebrated poetry collection by Colombian writer León de Greiff, known for its rich language, erudite allusions, and playful, experimental style.
  • D. Gjallarbrú
    Gjallarbrú is the mythic bridge in Norse mythology that spans the river Gjöll, marking the passage into the realm of the dead, Hel.
  • E. Mjermen
    Mjermen is a lake in southeastern Norway that forms part of the Haldenvassdraget watercourse system.
  • 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: Margit híd stop
Triple: [Budapest tram network, hasStop, Margit híd stop]
Generated description
Margit híd stop is a tram station in Budapest located near the Margaret Bridge, serving as a key interchange point on the city's tram network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Margit híd stop
Target entity description: Margit híd stop is a tram station in Budapest located near the Margaret Bridge, serving as a key interchange point on the city's tram network.
  • A. Dunántúl
    Dunántúl is the Hungarian name for Transdanubia, the large western region of Hungary lying west of the Danube River.
  • B. Maughold
    Maughold is a coastal parish and village on the Isle of Man known for its rugged cliffs, scenic coastline, and historic church with ancient Celtic crosses.
  • C. Fárrago
    Fárrago is a celebrated poetry collection by Colombian writer León de Greiff, known for its rich language, erudite allusions, and playful, experimental style.
  • D. Gjallarbrú
    Gjallarbrú is the mythic bridge in Norse mythology that spans the river Gjöll, marking the passage into the realm of the dead, Hel.
  • E. Mjermen
    Mjermen is a lake in southeastern Norway that forms part of the Haldenvassdraget watercourse system.
  • 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_69d85cc6cf40819091f4a5facee1ebe6 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04a9551288190a583e8291c35f521 completed April 16, 2026, 2:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff4560008c81908ebd278c3dc45045 completed May 9, 2026, 2:32 p.m.
NEDg Description generation batch_69ff47aa0bb081908f67e9dae9bc7b27 completed May 9, 2026, 2:41 p.m.
NED2 Entity disambiguation (via description) batch_69ff480d81b881908eb3a51f1e7280b0 completed May 9, 2026, 2:43 p.m.
Created at: April 10, 2026, 4:08 a.m.