Triple

T9703809
Position Surface form Disambiguated ID Type / Status
Subject Fehér (White) River region E234845 entity
Predicate namedAfter P63 FINISHED
Object Fehér (White) River
The Fehér (White) River is a watercourse in Central or Eastern Europe whose name, meaning “white,” reflects the characteristic appearance or clarity of its waters and lends its name to the surrounding region.
E2285104 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: Fehér (White) River | Statement: [Fehér (White) River region, namedAfter, Fehér (White) River]
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: Fehér (White) River
Triple: [Fehér (White) River region, namedAfter, Fehér (White) River]
Generated description
The Fehér (White) River is a watercourse in Central or Eastern Europe whose name, meaning “white,” reflects the characteristic appearance or clarity of its waters and lends its name to the surrounding region.

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_69ca84cc78808190a56f3402b7c139a7 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9d73a0148190ad4178fd462cdd9c completed April 1, 2026, 10:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a44c768932c8190b0199ce47268a47f completed July 1, 2026, 7:53 a.m.
NEDg Description generation batch_6a44c83089648190a42c95bad65f6d7d completed July 1, 2026, 7:56 a.m.
NED2 Entity disambiguation (via description) batch_6a44c91500ac8190873ba9dbe613fb3e completed July 1, 2026, 8 a.m.
Created at: March 30, 2026, 8:18 p.m.