Triple

T28153323
Position Surface form Disambiguated ID Type / Status
Subject Western Tehran E714679 entity
Predicate hasTransportInfrastructure P2560 FINISHED
Object Sattari Expressway
Sattari Expressway is a major urban highway in Tehran that helps connect western districts with other key parts of the city and its road network.
E1869827 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: Sattari Expressway | Statement: [Western Tehran, hasTransportInfrastructure, Sattari Expressway]
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: Sattari Expressway
Triple: [Western Tehran, hasTransportInfrastructure, Sattari Expressway]
Generated description
Sattari Expressway is a major urban highway in Tehran that helps connect western districts with other key parts of the city and its road network.

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_69efd6b033208190bf74f80a147e2092 completed April 27, 2026, 9:35 p.m.
NER Named-entity recognition batch_69f641789c90819081eb1c857d032025 completed May 2, 2026, 6:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25f0e5676c81908f306e37a08bd6fc completed June 7, 2026, 10:29 p.m.
NEDg Description generation batch_6a25f552f99881909b71511c1e143e8e completed June 7, 2026, 10:48 p.m.
NED2 Entity disambiguation (via description) batch_6a25f92f6744819093a671170bd83115 completed June 7, 2026, 11:05 p.m.
Created at: April 27, 2026, 10 p.m.