Triple

T36097284
Position Surface form Disambiguated ID Type / Status
Subject Hainburg an der Donau E1044097 entity
Predicate partOf P40 FINISHED
Object Marchfeld region
The Marchfeld region is a fertile lowland area in eastern Lower Austria, known for its intensive agriculture and historic role as a strategic corridor along the Danube between Vienna and Bratislava.
E2168390 NE FINISHED

How this triple was built (2 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: Marchfeld region | Statement: [Hainburg an der Donau, partOf, Marchfeld region]
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: Marchfeld region
Triple: [Hainburg an der Donau, partOf, Marchfeld region]
Generated description
The Marchfeld region is a fertile lowland area in eastern Lower Austria, known for its intensive agriculture and historic role as a strategic corridor along the Danube between Vienna and Bratislava.

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_69f76e32d60c8190ba781ffaaab4aa3d completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b28decac8190894f4c63977f9d7a completed May 3, 2026, 8:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38d54aab248190a865e10399e92f5a completed June 22, 2026, 6:25 a.m.
NEDg Description generation batch_6a38d5e83b58819080bd6a95a17f6b2b completed June 22, 2026, 6:27 a.m.
NED2 Entity disambiguation (via description) batch_6a38d681cf388190896a30e2b0939181 completed June 22, 2026, 6:30 a.m.
Created at: May 3, 2026, 4:08 p.m.