Triple

T36225191
Position Surface form Disambiguated ID Type / Status
Subject Igumale E1047964 entity
Predicate locatedInAdministrativeEntity P40 FINISHED
Object Ado Local Government Area
Ado Local Government Area is an administrative region in Benue State, Nigeria, comprising several towns and communities including Igumale.
E2175889 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: Ado Local Government Area | Statement: [Igumale, locatedInAdministrativeEntity, Ado Local Government 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: Ado Local Government Area
Triple: [Igumale, locatedInAdministrativeEntity, Ado Local Government Area]
Generated description
Ado Local Government Area is an administrative region in Benue State, Nigeria, comprising several towns and communities including Igumale.

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_69f76e42c878819095c8d19c0267fb87 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b59f00a08190b4a640552f794246 completed May 3, 2026, 8:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a394d34d0d481909fb22f17afd87f3b completed June 22, 2026, 2:56 p.m.
NEDg Description generation batch_6a394e193f4c81908694652d7126698d completed June 22, 2026, 3 p.m.
NED2 Entity disambiguation (via description) batch_6a3968453570819084081dc21fc59a21 completed June 22, 2026, 4:52 p.m.
Created at: May 3, 2026, 4:09 p.m.