Triple

T23097691
Position Surface form Disambiguated ID Type / Status
Subject Targovishte E575939 entity
Predicate administrativeCenterOf P383 FINISHED
Object Targovishte Municipality
Targovishte Municipality is a local administrative unit in northeastern Bulgaria that encompasses the town of Targovishte and surrounding settlements.
E1618512 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: Targovishte Municipality | Statement: [Targovishte, administrativeCenterOf, Targovishte Municipality]
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: Targovishte Municipality
Triple: [Targovishte, administrativeCenterOf, Targovishte Municipality]
Generated description
Targovishte Municipality is a local administrative unit in northeastern Bulgaria that encompasses the town of Targovishte and surrounding settlements.

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_69e245c060b48190a9bd61a47a16db17 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f18de61c7c8190809920fa1071935f completed April 29, 2026, 4:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f961a4e9c819098208116f8b1d293 completed May 21, 2026, 11:32 p.m.
NEDg Description generation batch_6a0f99eeed5c8190b0143c3734bf9b6c completed May 21, 2026, 11:49 p.m.
NED2 Entity disambiguation (via description) batch_6a0f9b0e3e588190bcbbdfea80ee54f6 completed May 21, 2026, 11:53 p.m.
Created at: April 17, 2026, 3:57 p.m.