Triple

T11133311
Position Surface form Disambiguated ID Type / Status
Subject Unstrut E263342 entity
Predicate hasTributary P415 FINISHED
Object Lossa
Lossa is a small river in central Germany that serves as a tributary of the Unstrut.
 E907875 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: Lossa | Statement: [Unstrut, hasTributary, Lossa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lossa
Context triple: [Unstrut, hasTributary, Lossa]
  • A. Agarfa
    Agarfa is a town and district in Ethiopia’s Oromia Region, situated within the Bale Zone and known for its agricultural and pastoral communities.
  • B. Urrugne
    Urrugne is a commune in the Pyrénées-Atlantiques department of southwestern France, located in the Basque Country near the Atlantic coast and the Spanish border.
  • C. Munxar
    Munxar is a small village on the island of Gozo in Malta, known for its rural character and scenic coastal surroundings.
  • D. Lödöse
    Lödöse is a historic Swedish town that was one of the country’s earliest and most important medieval trading centers, located in the province of Västergötland.
  • E. Hassela
    Hassela is a small rural locality in northern Sweden known for its forested landscape and nearby ski and outdoor recreation areas.
  • 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: Lossa
Triple: [Unstrut, hasTributary, Lossa]
Generated description
Lossa is a small river in central Germany that serves as a tributary of the Unstrut.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lossa
Target entity description: Lossa is a small river in central Germany that serves as a tributary of the Unstrut.
  • A. Agarfa
    Agarfa is a town and district in Ethiopia’s Oromia Region, situated within the Bale Zone and known for its agricultural and pastoral communities.
  • B. Urrugne
    Urrugne is a commune in the Pyrénées-Atlantiques department of southwestern France, located in the Basque Country near the Atlantic coast and the Spanish border.
  • C. Munxar
    Munxar is a small village on the island of Gozo in Malta, known for its rural character and scenic coastal surroundings.
  • D. Lödöse
    Lödöse is a historic Swedish town that was one of the country’s earliest and most important medieval trading centers, located in the province of Västergötland.
  • E. Hassela
    Hassela is a small rural locality in northern Sweden known for its forested landscape and nearby ski and outdoor recreation areas.
  • 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_69d6aa9c0ba08190bbd19c217489b755 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8347a248190837e8c26f25f553a completed April 9, 2026, 5:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69e441f00d7c8190a8fe8e0c1169e6b0 completed April 19, 2026, 2:46 a.m.
NEDg Description generation batch_69e44c09163481909d6a469b1e50b6ff completed April 19, 2026, 3:29 a.m.
NED2 Entity disambiguation (via description) batch_69e4519f4d408190be9863c72006ecad completed April 19, 2026, 3:53 a.m.
Created at: April 8, 2026, 9:28 p.m.