Triple

T2640825
Position Surface form Disambiguated ID Type / Status
Subject Oyo State E62860 entity
Predicate hasTown P847 FINISHED
Object Eruwa
Eruwa is a town in southwestern Nigeria known as an agrarian community and local commercial center within Oyo State.
 E286193 NE FINISHED

How this triple was built (4 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: Eruwa | Statement: [Oyo State, hasTown, Eruwa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Eruwa
Context triple: [Oyo State, hasTown, Eruwa]
  • A. Etiwanda
    Etiwanda is a historic former community in Southern California, now part of the city of Rancho Cucamonga, known for its early role in citrus agriculture and irrigation development.
  • B. Ouaddaï
    Ouaddaï is an eastern region of Chad known historically as the center of the former Wadai Sultanate and for its strategic location near the Sudanese border.
  • C. Wele-Nzas
    Wele-Nzas is a province in mainland Equatorial Guinea known for its forests, border location near Gabon and Cameroon, and the city of Mongomo.
  • D. Ndowe
    Ndowe is a Bantu language spoken by the Ndowe people along the coastal region of Equatorial Guinea.
  • E. Ubangian
    Ubangian is a proposed branch of the Niger-Congo (sometimes considered an independent) language family spoken primarily in the Central African Republic and neighboring regions.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Eruwa
Triple: [Oyo State, hasTown, Eruwa]
Generated description
Eruwa is a town in southwestern Nigeria known as an agrarian community and local commercial center within Oyo State.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Eruwa
Target entity description: Eruwa is a town in southwestern Nigeria known as an agrarian community and local commercial center within Oyo State.
  • A. Etiwanda
    Etiwanda is a historic former community in Southern California, now part of the city of Rancho Cucamonga, known for its early role in citrus agriculture and irrigation development.
  • B. Ouaddaï
    Ouaddaï is an eastern region of Chad known historically as the center of the former Wadai Sultanate and for its strategic location near the Sudanese border.
  • C. Wele-Nzas
    Wele-Nzas is a province in mainland Equatorial Guinea known for its forests, border location near Gabon and Cameroon, and the city of Mongomo.
  • D. Ndowe
    Ndowe is a Bantu language spoken by the Ndowe people along the coastal region of Equatorial Guinea.
  • E. Ubangian
    Ubangian is a proposed branch of the Niger-Congo (sometimes considered an independent) language family spoken primarily in the Central African Republic and neighboring regions.
  • F. None of above. chosen

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_69ab4c3f2dcc819082df80f5e032f690 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abd8fc8ee881908a9f6820d8934a62 completed March 7, 2026, 7:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69af98bd689481908568d35baac1e065 completed March 10, 2026, 4:06 a.m.
NEDg Description generation batch_69af99c237548190838559ccac95f1c5 completed March 10, 2026, 4:10 a.m.
NED2 Entity disambiguation (via description) batch_69af9a5938b48190820f37f2e2280438 completed March 10, 2026, 4:13 a.m.
Created at: March 6, 2026, 9:53 p.m.