Triple

T26237577
Position Surface form Disambiguated ID Type / Status
Subject Treaties of Benin E656211 entity
Predicate enforcedBy P1115 FINISHED
Object courts of Benin
The courts of Benin are the national judicial bodies responsible for interpreting and applying the country’s laws and international treaties within its legal system.
 E1714922 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: courts of Benin | Statement: [Treaties of Benin, enforcedBy, courts of Benin]
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: courts of Benin
Triple: [Treaties of Benin, enforcedBy, courts of Benin]
Generated description
The courts of Benin are the national judicial bodies responsible for interpreting and applying the country’s laws and international treaties within its legal system.

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_69ee5b4b8b408190993da38c0067cc8d completed April 26, 2026, 6:36 p.m.
NER Named-entity recognition batch_69f60d8c94448190a269c19e912dbecc completed May 2, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11859bfa288190aa1d407b8fcd6393 completed May 23, 2026, 10:46 a.m.
NEDg Description generation batch_6a11863dfad48190903b8defdb1f64f6 completed May 23, 2026, 10:49 a.m.
NED2 Entity disambiguation (via description) batch_6a1186d8c7bc81909c851862b3a29e13 completed May 23, 2026, 10:52 a.m.
Created at: April 26, 2026, 9:02 p.m.