Triple

T31188805
Position Surface form Disambiguated ID Type / Status
Subject Pest-Pilis-Solt-Kiskun County E795125 entity
Predicate predecessor P97 FINISHED
Object Pilis County
Pilis County was a historical administrative region in the Kingdom of Hungary that later became part of the larger Pest-Pilis-Solt-Kiskun County.
E1962924 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: Pilis County | Statement: [Pest-Pilis-Solt-Kiskun County, predecessor, Pilis County]
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: Pilis County
Triple: [Pest-Pilis-Solt-Kiskun County, predecessor, Pilis County]
Generated description
Pilis County was a historical administrative region in the Kingdom of Hungary that later became part of the larger Pest-Pilis-Solt-Kiskun County.

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_69f224d7a6a481908187c4362a8a525f completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69913d91c81908d00dc873428367b completed May 3, 2026, 12:38 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b07563c348190a05e5d43df7f10a9 completed June 11, 2026, 7:07 p.m.
NEDg Description generation batch_6a2b095700e4819083943c7b261e768a completed June 11, 2026, 7:15 p.m.
NED2 Entity disambiguation (via description) batch_6a2b09b430388190832809716830d009 completed June 11, 2026, 7:17 p.m.
Created at: April 29, 2026, 9:08 p.m.