Triple

T35308685
Position Surface form Disambiguated ID Type / Status
Subject Ministry of Culture of Syria E1019706 entity
Predicate officialName P66 FINISHED
Object Ministry of Culture
The Ministry of Culture is the Syrian government body responsible for overseeing cultural policy, heritage preservation, and the promotion of arts and cultural activities across the country.
E2135114 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: Ministry of Culture | Statement: [Ministry of Culture of Syria, officialName, Ministry of Culture]
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: Ministry of Culture
Triple: [Ministry of Culture of Syria, officialName, Ministry of Culture]
Generated description
The Ministry of Culture is the Syrian government body responsible for overseeing cultural policy, heritage preservation, and the promotion of arts and cultural activities across the country.

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_69f76de8b4c48190ae504b86185c474c completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f79052ed048190afc63b2c29b9758b completed May 3, 2026, 6:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3819efe3c881908c3ddb151fb8464c completed June 21, 2026, 5:05 p.m.
NEDg Description generation batch_6a381b546e2c81909a66c8348d129f5a completed June 21, 2026, 5:11 p.m.
NED2 Entity disambiguation (via description) batch_6a381be1481c8190946a129038907bdc completed June 21, 2026, 5:14 p.m.
Created at: May 3, 2026, 4:03 p.m.