Triple

T4434669
Position Surface form Disambiguated ID Type / Status
Subject Buskerud E95618 entity
Predicate contains P35 FINISHED
Object Sigdal
Sigdal is a rural municipality in southeastern Norway known for its forested landscapes, lakes, and traditional farming communities.
 E440170 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: Sigdal | Statement: [Buskerud, contains, Sigdal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sigdal
Context triple: [Buskerud, contains, Sigdal]
  • A. Sardoal
    Sardoal is a small Portuguese municipality known for its historic village center and traditional religious and cultural festivities, located in the Centro Region of Portugal.
  • B. Solodamu
    Solodamu is a small coastal village located on Kadavu Island in Fiji, known for its traditional Fijian lifestyle and surrounding natural beauty.
  • C. Dausa
    Dausa is a town and district headquarters in the Indian state of Rajasthan, known for its historical forts, stepwells, and proximity to Jaipur.
  • D. Mora
    Mora is a surname of Hungarian origin most notably borne by the German-Hungarian writer Terézia Mora.
  • E. Mora
    Mora is a municipality in Portugal known for its rural Alentejo landscapes, traditional villages, and proximity to the Montargil reservoir.
  • 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: Sigdal
Triple: [Buskerud, contains, Sigdal]
Generated description
Sigdal is a rural municipality in southeastern Norway known for its forested landscapes, lakes, and traditional farming communities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sigdal
Target entity description: Sigdal is a rural municipality in southeastern Norway known for its forested landscapes, lakes, and traditional farming communities.
  • A. Sardoal
    Sardoal is a small Portuguese municipality known for its historic village center and traditional religious and cultural festivities, located in the Centro Region of Portugal.
  • B. Solodamu
    Solodamu is a small coastal village located on Kadavu Island in Fiji, known for its traditional Fijian lifestyle and surrounding natural beauty.
  • C. Dausa
    Dausa is a town and district headquarters in the Indian state of Rajasthan, known for its historical forts, stepwells, and proximity to Jaipur.
  • D. Mora
    Mora is a surname of Hungarian origin most notably borne by the German-Hungarian writer Terézia Mora.
  • E. Mora
    Mora is a municipality in Portugal known for its rural Alentejo landscapes, traditional villages, and proximity to the Montargil reservoir.
  • 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_69b3453ea2b48190a26f154b3b8fece5 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35588e99881908fea7b71a33e2bb6 completed March 13, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69b6137378dc8190900c8fda2693c4da completed March 15, 2026, 2:03 a.m.
NEDg Description generation batch_69b61439a86c8190849c5af718ddc647 completed March 15, 2026, 2:06 a.m.
NED2 Entity disambiguation (via description) batch_69b614d6106c81908a601f540622f934 completed March 15, 2026, 2:09 a.m.
Created at: March 12, 2026, 11:31 p.m.