Triple

T10429678
Position Surface form Disambiguated ID Type / Status
Subject Dals-Ed Municipality E245876 entity
Predicate hasSettlement P1068 FINISHED
Object Ed
Ed is a small locality in western Sweden that serves as the administrative center of Dals-Ed Municipality in Västra Götaland County.
 E866583 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: Ed | Statement: [Dals-Ed Municipality, hasSettlement, Ed]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ed
Context triple: [Dals-Ed Municipality, hasSettlement, Ed]
  • A. Ed
    Ed is a common masculine given name, typically used as a short form of names such as Edward, Edwin, or Edmund.
  • B. ED
    ED is the standard abbreviation for the Eredivisie, the top professional football league in the Netherlands.
  • C. ED
    ED is a classic line-based text editor commonly used in Unix-like operating systems, known for its minimal interface and suitability for scripting and low-resource environments.
  • D. ED
    ED is the federal agency responsible for establishing policy, administering, and coordinating most education-related programs in the United States.
  • E. ED
    ED is the official station code for Ede-Wageningen railway station in the Netherlands.
  • 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: Ed
Triple: [Dals-Ed Municipality, hasSettlement, Ed]
Generated description
Ed is a small locality in western Sweden that serves as the administrative center of Dals-Ed Municipality in Västra Götaland County.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ed
Target entity description: Ed is a small locality in western Sweden that serves as the administrative center of Dals-Ed Municipality in Västra Götaland County.
  • A. Ed
    Ed is a common masculine given name, typically used as a short form of names such as Edward, Edwin, or Edmund.
  • B. ED
    ED is the standard abbreviation for the Eredivisie, the top professional football league in the Netherlands.
  • C. ED
    ED is a classic line-based text editor commonly used in Unix-like operating systems, known for its minimal interface and suitability for scripting and low-resource environments.
  • D. ED
    ED is the federal agency responsible for establishing policy, administering, and coordinating most education-related programs in the United States.
  • E. ED
    ED is the official station code for Ede-Wageningen railway station in the Netherlands.
  • 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_69d381bf3dc08190bf35a2643e4e8f22 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4ea4b4b5881908ae23f8efeea482b completed April 7, 2026, 11:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69d8dc374f6c8190a44b9da27be343e4 completed April 10, 2026, 11:17 a.m.
NEDg Description generation batch_69d8e8c683608190aa4333ed38e79f53 completed April 10, 2026, 12:10 p.m.
NED2 Entity disambiguation (via description) batch_69d901c7684c8190837ed9ef0c2428af completed April 10, 2026, 1:57 p.m.
Created at: April 6, 2026, 12:13 p.m.