Triple

T30619501
Position Surface form Disambiguated ID Type / Status
Subject Shedgum E779406 entity
Predicate associatedWith P37 FINISHED
Object Haradh production area
The Haradh production area is a major oil and gas producing region in Saudi Arabia operated by Saudi Aramco, known for its large-scale hydrocarbon fields and facilities.
 E1925041 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: Haradh production area | Statement: [Shedgum, associatedWith, Haradh production area]
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: Haradh production area
Triple: [Shedgum, associatedWith, Haradh production area]
Generated description
The Haradh production area is a major oil and gas producing region in Saudi Arabia operated by Saudi Aramco, known for its large-scale hydrocarbon fields and facilities.

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_69f224a3307081909a6dca8ca75dbf48 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f689ed5b9c81909976d061f71d782a completed May 2, 2026, 11:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2863e405788190871cc7b400076e26 completed June 9, 2026, 7:05 p.m.
NEDg Description generation batch_6a2864b0d14881909640d9616d96f1e0 completed June 9, 2026, 7:08 p.m.
NED2 Entity disambiguation (via description) batch_6a286552416081909d1352b5b418beeb completed June 9, 2026, 7:11 p.m.
Created at: April 29, 2026, 8:26 p.m.