Triple

T21807742
Position Surface form Disambiguated ID Type / Status
Subject Emmaboda Municipality E538390 entity
Predicate hasSettlement P1068 FINISHED
Object Eriksmåla
Eriksmåla is a small locality in southern Sweden, situated in Kalmar County within Emmaboda Municipality.
E1502293 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: Eriksmåla | Statement: [Emmaboda Municipality, hasSettlement, Eriksmåla]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eriksmåla
Context triple: [Emmaboda Municipality, hasSettlement, Eriksmåla]
  • A. Byrkjelo
    Byrkjelo is a small village in Vestland county, Norway, known for its scenic valley setting and as a local transport and agricultural hub between major fjord and inland areas.
  • B. Bekkestua
    Bekkestua is a suburban center in Bærum, Norway, functioning as a local commercial and transport hub just west of Oslo.
  • C. Tyssedal
    Tyssedal is a small industrial village in Vestland county, Norway, known for its historic hydropower facilities and scenic location by the Sørfjorden.
  • D. Hasselvika
    Hasselvika is a small coastal village in the former Agdenes municipality in Trøndelag county, central Norway.
  • E. Meråker
    Meråker is a mountainous municipality in Trøndelag county, Norway, known for its outdoor recreation, skiing facilities, and proximity to the Swedish border.
  • 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: Eriksmåla
Triple: [Emmaboda Municipality, hasSettlement, Eriksmåla]
Generated description
Eriksmåla is a small locality in southern Sweden, situated in Kalmar County within Emmaboda Municipality.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Eriksmåla
Target entity description: Eriksmåla is a small locality in southern Sweden, situated in Kalmar County within Emmaboda Municipality.
  • A. Byrkjelo
    Byrkjelo is a small village in Vestland county, Norway, known for its scenic valley setting and as a local transport and agricultural hub between major fjord and inland areas.
  • B. Bekkestua
    Bekkestua is a suburban center in Bærum, Norway, functioning as a local commercial and transport hub just west of Oslo.
  • C. Tyssedal
    Tyssedal is a small industrial village in Vestland county, Norway, known for its historic hydropower facilities and scenic location by the Sørfjorden.
  • D. Hasselvika
    Hasselvika is a small coastal village in the former Agdenes municipality in Trøndelag county, central Norway.
  • E. Meråker
    Meråker is a mountainous municipality in Trøndelag county, Norway, known for its outdoor recreation, skiing facilities, and proximity to the Swedish border.
  • 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_69e0c473f0f8819086c9d1b4a143bd67 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f078047ca88190a0efa4bc7f2faf80 completed April 28, 2026, 9:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0a3e86d8ec81908c8a5a63903e44a4 completed May 17, 2026, 10:17 p.m.
NEDg Description generation batch_6a0a3f4358d48190a88208a55d19a9ef completed May 17, 2026, 10:20 p.m.
NED2 Entity disambiguation (via description) batch_6a0a404206e0819080c640619cd277ab completed May 17, 2026, 10:25 p.m.
Created at: April 16, 2026, 6:53 p.m.