Triple

T33400140
Position Surface form Disambiguated ID Type / Status
Subject Beth Zabday E855272 entity
Predicate locatedOn P40 FINISHED
Object plateau of Tur Abdin
The plateau of Tur Abdin is a hilly region in southeastern Turkey historically known as a heartland of Syriac Orthodox Christianity and its ancient monasteries.
E2049178 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: plateau of Tur Abdin | Statement: [Beth Zabday, locatedOn, plateau of Tur Abdin]
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: plateau of Tur Abdin
Triple: [Beth Zabday, locatedOn, plateau of Tur Abdin]
Generated description
The plateau of Tur Abdin is a hilly region in southeastern Turkey historically known as a heartland of Syriac Orthodox Christianity and its ancient monasteries.

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_69f3496e3f1c8190bcecfa82aa9d17ff completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6e41396848190b73aa31c92f13fe1 completed May 3, 2026, 5:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3576f57ee08190a8789853e3940533 completed June 19, 2026, 5:05 p.m.
NEDg Description generation batch_6a3578085b248190bc4a4deeddc80efb completed June 19, 2026, 5:10 p.m.
NED2 Entity disambiguation (via description) batch_6a3578b81d808190bf05400add1c794a completed June 19, 2026, 5:13 p.m.
Created at: May 1, 2026, 1:35 a.m.