Triple

T32048536
Position Surface form Disambiguated ID Type / Status
Subject Sattar Khan E818419 entity
Predicate hasMonument P105 FINISHED
Object Sattar Khan statue in Tabriz
The Sattar Khan statue in Tabriz is a public monument honoring the famed Iranian constitutional revolutionary leader Sattar Khan, located in his home city of Tabriz.
E1988937 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: Sattar Khan statue in Tabriz | Statement: [Sattar Khan, hasMonument, Sattar Khan statue in Tabriz]
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: Sattar Khan statue in Tabriz
Triple: [Sattar Khan, hasMonument, Sattar Khan statue in Tabriz]
Generated description
The Sattar Khan statue in Tabriz is a public monument honoring the famed Iranian constitutional revolutionary leader Sattar Khan, located in his home city of Tabriz.

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_69f348fcfb648190859f6be5e04b7cfe completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b4c5e18c8190b03bbde2092b701a completed May 3, 2026, 2:36 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2ed5014dc48190a867e1417199d589 completed June 14, 2026, 4:21 p.m.
NEDg Description generation batch_6a2ed5c07e34819098385a0d7a928fa4 completed June 14, 2026, 4:24 p.m.
NED2 Entity disambiguation (via description) batch_6a2ed7379d088190b7481d5c7eb61b9f completed June 14, 2026, 4:30 p.m.
Created at: May 1, 2026, 12:20 a.m.