Triple

T38239793
Position Surface form Disambiguated ID Type / Status
Subject Isoko South E1013728 entity
Predicate hasOilField P27831 FINISHED
Object Emede oil field
Emede oil field is a petroleum-producing field located in the Emede community of Isoko South, Delta State, Nigeria.
E2261018 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: Emede oil field | Statement: [Isoko South, hasOilField, Emede oil field]
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: Emede oil field
Triple: [Isoko South, hasOilField, Emede oil field]
Generated description
Emede oil field is a petroleum-producing field located in the Emede community of Isoko South, Delta State, Nigeria.

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_69f76dd72a248190a5fe18db2bd1eb15 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69fcb17ebfd081908b33491c49561f18 completed May 7, 2026, 3:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41855fab508190bfc40c55cd38956a completed June 28, 2026, 8:34 p.m.
NEDg Description generation batch_6a41877545d0819085b016167f558c98 completed June 28, 2026, 8:43 p.m.
NED2 Entity disambiguation (via description) batch_6a4187f33cc48190a7c85c5255cc5db9 completed June 28, 2026, 8:45 p.m.
Created at: May 3, 2026, 4:30 p.m.