Triple

T24852071
Position Surface form Disambiguated ID Type / Status
Subject Natella Abashwili E621914 entity
Predicate spouse P13 FINISHED
Object Governor Georgi Abashwili
Governor Georgi Abashwili is a fictional high-ranking official in Bertolt Brecht’s play "The Caucasian Chalk Circle," whose downfall and abandoned child drive the drama’s central conflict.
E1654320 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: Governor Georgi Abashwili | Statement: [Natella Abashwili, spouse, Governor Georgi Abashwili]
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: Governor Georgi Abashwili
Triple: [Natella Abashwili, spouse, Governor Georgi Abashwili]
Generated description
Governor Georgi Abashwili is a fictional high-ranking official in Bertolt Brecht’s play "The Caucasian Chalk Circle," whose downfall and abandoned child drive the drama’s central conflict.

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_69e2fac297e481909d3aedc75f585e42 completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f422e5e44c8190aeff55a6be90a6cc completed May 1, 2026, 3:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a101c533540819094411da3f6178d1d completed May 22, 2026, 9:05 a.m.
NEDg Description generation batch_6a102814f838819094ed41d653039f72 completed May 22, 2026, 9:55 a.m.
NED2 Entity disambiguation (via description) batch_6a10294485508190a91d9ec391181047 completed May 22, 2026, 10 a.m.
Created at: April 18, 2026, 5:20 a.m.