Triple

T27623586
Position Surface form Disambiguated ID Type / Status
Subject Gagra E696142 entity
Predicate partOf P40 FINISHED
Object Gagra District
Gagra District is an administrative district in the northwestern part of Abkhazia, along the Black Sea coast and the border with Russia.
E1789743 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: Gagra District | Statement: [Gagra, partOf, Gagra District]
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: Gagra District
Triple: [Gagra, partOf, Gagra District]
Generated description
Gagra District is an administrative district in the northwestern part of Abkhazia, along the Black Sea coast and the border with Russia.

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_69ef59092c8881908114ad184248cc46 completed April 27, 2026, 12:39 p.m.
NER Named-entity recognition batch_69f630df75248190a445f3c76dd5056f completed May 2, 2026, 5:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12ec9909988190acff9e2e476c9199 completed May 24, 2026, 12:18 p.m.
NEDg Description generation batch_6a12ed49266881909fd55a7028ad6a1f completed May 24, 2026, 12:21 p.m.
NED2 Entity disambiguation (via description) batch_6a12ee215b4c8190aeef56575c0c0015 completed May 24, 2026, 12:25 p.m.
Created at: April 27, 2026, 2:16 p.m.