Triple

T31984982
Position Surface form Disambiguated ID Type / Status
Subject Semnan University E816695 entity
Predicate hasResearchCenter P40 FINISHED
Object desert studies research center
The desert studies research center is a specialized institute at Semnan University focused on researching arid environments, desertification, and sustainable development in desert regions.
E1987726 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: desert studies research center | Statement: [Semnan University, hasResearchCenter, desert studies research center]
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: desert studies research center
Triple: [Semnan University, hasResearchCenter, desert studies research center]
Generated description
The desert studies research center is a specialized institute at Semnan University focused on researching arid environments, desertification, and sustainable development in desert regions.

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_69f348f6a3008190bfb59ca695fd68e2 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b3ae2cb481909c375799c0ec5c07 completed May 3, 2026, 2:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2eb154b98081909e54829e4ca401b7 completed June 14, 2026, 1:49 p.m.
NEDg Description generation batch_6a2eb1e890dc8190b9948d105e53e444 completed June 14, 2026, 1:51 p.m.
NED2 Entity disambiguation (via description) batch_6a2eb29420988190a93593427ea8715a completed June 14, 2026, 1:54 p.m.
Created at: May 1, 2026, 12:12 a.m.