Triple

T2849753
Position Surface form Disambiguated ID Type / Status
Subject Seeland region E63063 entity
Predicate hasTown P847 FINISHED
Object Ins
Ins is a small Swiss municipality located in the Seeland region of the canton of Bern, known for its agricultural landscape and proximity to the lakes of Biel, Neuchâtel, and Murten.
 E302977 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: Ins | Statement: [Seeland region, hasTown, Ins]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ins
Context triple: [Seeland region, hasTown, Ins]
  • A. It
    It is a 1986 horror novel by Stephen King about a shape-shifting entity that terrorizes children in the town of Derry, Maine.
  • B. IN
    IN is the official two-letter United States Postal Service abbreviation for the state of Indiana.
  • C. IN
    IN is the two-letter ISO 3166-1 alpha-2 country code representing India in international standards and systems.
  • D. Sus
    Sus is a genus of mammals in the pig family that includes domestic pigs and several species of wild boar.
  • E. INST
    INST is the stock ticker symbol for Instructure, an education technology company best known for its Canvas learning management 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: Ins
Triple: [Seeland region, hasTown, Ins]
Generated description
Ins is a small Swiss municipality located in the Seeland region of the canton of Bern, known for its agricultural landscape and proximity to the lakes of Biel, Neuchâtel, and Murten.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ins
Target entity description: Ins is a small Swiss municipality located in the Seeland region of the canton of Bern, known for its agricultural landscape and proximity to the lakes of Biel, Neuchâtel, and Murten.
  • A. It
    It is a 1986 horror novel by Stephen King about a shape-shifting entity that terrorizes children in the town of Derry, Maine.
  • B. IN
    IN is the official two-letter United States Postal Service abbreviation for the state of Indiana.
  • C. IN
    IN is the two-letter ISO 3166-1 alpha-2 country code representing India in international standards and systems.
  • D. Sus
    Sus is a genus of mammals in the pig family that includes domestic pigs and several species of wild boar.
  • E. INST
    INST is the stock ticker symbol for Instructure, an education technology company best known for its Canvas learning management 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_69ab4c407c408190857d25e027155ce9 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdf41ac24819087c5b72e3b84117c completed March 7, 2026, 8:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69afe8df46c881909a5f0d1d0eef9a42 completed March 10, 2026, 9:48 a.m.
NEDg Description generation batch_69afe948ba148190a88126df32f16be2 completed March 10, 2026, 9:50 a.m.
NED2 Entity disambiguation (via description) batch_69b0018170908190976f849380841b17 completed March 10, 2026, 11:33 a.m.
Created at: March 6, 2026, 10:02 p.m.