Triple

T35242785
Position Surface form Disambiguated ID Type / Status
Subject Owerri Municipal E1017571 entity
Predicate leaderTitle P8 FINISHED
Object Local Government Chairman
The Local Government Chairman is the elected head of a local council responsible for administering grassroots governance, public services, and development initiatives within a specific local government area.
E2130962 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: Local Government Chairman | Statement: [Owerri Municipal, leaderTitle, Local Government Chairman]
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: Local Government Chairman
Triple: [Owerri Municipal, leaderTitle, Local Government Chairman]
Generated description
The Local Government Chairman is the elected head of a local council responsible for administering grassroots governance, public services, and development initiatives within a specific local government area.

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_69f76de235048190b990070c23c51b6b completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78f24b8048190ac4bea4af553256e completed May 3, 2026, 6:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38042388b881909cc79807154aa556 completed June 21, 2026, 3:32 p.m.
NEDg Description generation batch_6a3804c7440481908ab7c5be8df1c65f completed June 21, 2026, 3:35 p.m.
NED2 Entity disambiguation (via description) batch_6a38059a9cf88190a487032818a0ee14 completed June 21, 2026, 3:39 p.m.
Created at: May 3, 2026, 4:02 p.m.