Triple

T1415514
Position Surface form Disambiguated ID Type / Status
Subject Battle of Halmstad E31905 entity
Predicate location P40 FINISHED
Object Halmstad
Halmstad is a coastal city in southwestern Sweden known for its historic town center, harbor, and role as a strategic site in Scandinavian conflicts.
 E218044 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: Halmstad | Statement: [Battle of Halmstad, location, Halmstad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Halmstad
Context triple: [Battle of Halmstad, location, Halmstad]
  • A. Nyköping
    Nyköping is a historic coastal town in southeastern Sweden known for its medieval castle, harbor, and role as a regional administrative and cultural center.
  • B. Lund
    Lund is a common Scandinavian surname of Swedish origin.
  • C. Jönköping
    Jönköping is a city in southern Sweden, located at the southern end of Lake Vättern and known as a regional commercial and logistical hub.
  • D. Kalmar
    Kalmar is a historic coastal city in southeastern Sweden known for its medieval castle, role in the Kalmar Union, and connection to the island of Öland.
  • E. Trollhättan
    Trollhättan is a city in western Sweden known for its historic role in the automotive industry and as the longtime home of Saab Automobile’s main production facilities.
  • 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: Halmstad
Triple: [Battle of Halmstad, location, Halmstad]
Generated description
Halmstad is a coastal city in southwestern Sweden known for its historic town center, harbor, and role as a strategic site in Scandinavian conflicts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Halmstad
Target entity description: Halmstad is a coastal city in southwestern Sweden known for its historic town center, harbor, and role as a strategic site in Scandinavian conflicts.
  • A. Nyköping
    Nyköping is a historic coastal town in southeastern Sweden known for its medieval castle, harbor, and role as a regional administrative and cultural center.
  • B. Lund
    Lund is a common Scandinavian surname of Swedish origin.
  • C. Jönköping
    Jönköping is a city in southern Sweden, located at the southern end of Lake Vättern and known as a regional commercial and logistical hub.
  • D. Kalmar
    Kalmar is a historic coastal city in southeastern Sweden known for its medieval castle, role in the Kalmar Union, and connection to the island of Öland.
  • E. Trollhättan
    Trollhättan is a city in western Sweden known for its historic role in the automotive industry and as the longtime home of Saab Automobile’s main production facilities.
  • 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_69a49919a994819086528951bc224775 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c402b1648190b87802d9beb2712e completed March 1, 2026, 10:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69adfb8a58ec81908b2bb5c27283bafa completed March 8, 2026, 10:43 p.m.
NEDg Description generation batch_69adfc6aa96c81909ae3cff6c7ab7f79 completed March 8, 2026, 10:47 p.m.
NED2 Entity disambiguation (via description) batch_69adfcebbc808190a74f9082636bce11 completed March 8, 2026, 10:49 p.m.
Created at: March 1, 2026, 7:59 p.m.