Triple

T10644813
Position Surface form Disambiguated ID Type / Status
Subject Bages E250809 entity
Predicate containsMunicipality P852 FINISHED
Object Marganell
Marganell is a small municipality in the comarca of Bages in Catalonia, Spain, known for its rural character and proximity to the Montserrat mountain range.
 E878058 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: Marganell | Statement: [Bages, containsMunicipality, Marganell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Marganell
Context triple: [Bages, containsMunicipality, Marganell]
  • A. Manucium
    Manucium is an alternative historical name for Mamucium, the Roman-era fort and settlement that formed the origin of modern Manchester in northwest England.
  • B. Moraima
    Moraima was the wife of Boabdil, the last Nasrid ruler of the Emirate of Granada in late medieval Spain.
  • C. Mawanella
    Mawanella is a town in central Sri Lanka known as a key transit point on the Colombo–Kandy road and for its surrounding rubber and tea plantations.
  • D. Mylasa
    Mylasa was an important ancient city of Caria in southwestern Anatolia, known as a political and religious center, particularly for the worship of Zeus.
  • E. Marella
    Marella is an Italian feminine given name, notably borne by Marella Agnelli, a prominent socialite, art collector, and style icon.
  • 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: Marganell
Triple: [Bages, containsMunicipality, Marganell]
Generated description
Marganell is a small municipality in the comarca of Bages in Catalonia, Spain, known for its rural character and proximity to the Montserrat mountain range.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Marganell
Target entity description: Marganell is a small municipality in the comarca of Bages in Catalonia, Spain, known for its rural character and proximity to the Montserrat mountain range.
  • A. Manucium
    Manucium is an alternative historical name for Mamucium, the Roman-era fort and settlement that formed the origin of modern Manchester in northwest England.
  • B. Moraima
    Moraima was the wife of Boabdil, the last Nasrid ruler of the Emirate of Granada in late medieval Spain.
  • C. Mawanella
    Mawanella is a town in central Sri Lanka known as a key transit point on the Colombo–Kandy road and for its surrounding rubber and tea plantations.
  • D. Mylasa
    Mylasa was an important ancient city of Caria in southwestern Anatolia, known as a political and religious center, particularly for the worship of Zeus.
  • E. Marella
    Marella is an Italian feminine given name, notably borne by Marella Agnelli, a prominent socialite, art collector, and style icon.
  • 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_69d6aa5a4c4881908f39be6efe5981e5 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6dfd04ca88190ac4fffd13c1f33a8 completed April 8, 2026, 11:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69d97a4dd4e48190ba7d0291686702e6 completed April 10, 2026, 10:31 p.m.
NEDg Description generation batch_69d97cc20448819094d650b9c1067dca completed April 10, 2026, 10:42 p.m.
NED2 Entity disambiguation (via description) batch_69d97e0cda0c8190af5013b971b2ad3c completed April 10, 2026, 10:47 p.m.
Created at: April 8, 2026, 9:05 p.m.