Triple
T12795716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abeokuta South |
E305883
|
entity |
| Predicate | hasUrbanArea |
P316
|
FINISHED |
| Object |
Sapon
Sapon is a major commercial and transportation hub in Abeokuta, Ogun State, Nigeria.
|
E1001992
|
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: Sapon | Statement: [Abeokuta South, hasUrbanArea, Sapon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sapon Context triple: [Abeokuta South, hasUrbanArea, Sapon]
-
A.
Saponi
The Saponi are a Native American people historically located in the Piedmont region of present-day Virginia and North Carolina, culturally and linguistically related to other Siouan-speaking tribes of the area.
-
B.
Saravena
Saravena is a Colombian town and municipality located in the northeastern oil-producing and conflict-affected region near the border with Venezuela.
-
C.
Sosanya
Sosanya is a surname most notably associated with British actress Nina Sosanya, known for her extensive work in television, film, and theatre.
-
D.
Sophanene
Sophanene is an alternate name for Sophene, an ancient historical region located in what is now eastern Turkey and parts of Armenia.
-
E.
Sulien
Sulien is a Welsh saint traditionally venerated as a local holy figure associated with churches in Wales.
- 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: Sapon Triple: [Abeokuta South, hasUrbanArea, Sapon]
Generated description
Sapon is a major commercial and transportation hub in Abeokuta, Ogun State, Nigeria.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sapon Target entity description: Sapon is a major commercial and transportation hub in Abeokuta, Ogun State, Nigeria.
-
A.
Saponi
The Saponi are a Native American people historically located in the Piedmont region of present-day Virginia and North Carolina, culturally and linguistically related to other Siouan-speaking tribes of the area.
-
B.
Saravena
Saravena is a Colombian town and municipality located in the northeastern oil-producing and conflict-affected region near the border with Venezuela.
-
C.
Sosanya
Sosanya is a surname most notably associated with British actress Nina Sosanya, known for her extensive work in television, film, and theatre.
-
D.
Sophanene
Sophanene is an alternate name for Sophene, an ancient historical region located in what is now eastern Turkey and parts of Armenia.
-
E.
Sulien
Sulien is a Welsh saint traditionally venerated as a local holy figure associated with churches in Wales.
- 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_69d7bdf366888190a8cccb982606889c |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e6db68481909a2ca8da1287f3e0 |
completed | April 10, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6850d6ebc8190aaffcac09f4b15eb |
completed | May 2, 2026, 11:13 p.m. |
| NEDg | Description generation | batch_69f6863fada48190afe2ff7896a60094 |
completed | May 2, 2026, 11:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f686bcac94819088782273effbb06a |
completed | May 2, 2026, 11:20 p.m. |
Created at: April 9, 2026, 5:30 p.m.