Triple
T12712203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ado-Odo/Ota |
E303746
|
entity |
| Predicate | hasMajorTown |
P316
|
FINISHED |
| Object |
Sango-Ota
Sango-Ota is a major industrial and residential town in Ogun State, southwestern Nigeria, known for its manufacturing activities and proximity to Lagos.
|
E1249255
|
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: Sango-Ota | Statement: [Ado-Odo/Ota, hasMajorTown, Sango-Ota]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sango-Ota Context triple: [Ado-Odo/Ota, hasMajorTown, Sango-Ota]
-
A.
Tatsuno
Tatsuno is a city in western Japan known for its traditional soy sauce production and historic townscape within Hyogo Prefecture.
-
B.
Nonoichi
Nonoichi is a city in Ishikawa Prefecture, Japan, known for its residential character and proximity to the regional hub of Kanazawa.
-
C.
Tsuchiura
Tsuchiura is a city in Ibaraki Prefecture, Japan, known for its location on the shores of Lake Kasumigaura and its annual national fireworks competition.
-
D.
Ichigaya
Ichigaya is a central Tokyo district known for its major railway station, government and educational institutions, and proximity to the Imperial Palace area.
-
E.
Kamiyama
Kamiyama is a Japanese surname borne by various individuals, including artists, athletes, and public figures.
- 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: Sango-Ota Triple: [Ado-Odo/Ota, hasMajorTown, Sango-Ota]
Generated description
Sango-Ota is a major industrial and residential town in Ogun State, southwestern Nigeria, known for its manufacturing activities and proximity to Lagos.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sango-Ota Target entity description: Sango-Ota is a major industrial and residential town in Ogun State, southwestern Nigeria, known for its manufacturing activities and proximity to Lagos.
-
A.
Tatsuno
Tatsuno is a city in western Japan known for its traditional soy sauce production and historic townscape within Hyogo Prefecture.
-
B.
Nonoichi
Nonoichi is a city in Ishikawa Prefecture, Japan, known for its residential character and proximity to the regional hub of Kanazawa.
-
C.
Tsuchiura
Tsuchiura is a city in Ibaraki Prefecture, Japan, known for its location on the shores of Lake Kasumigaura and its annual national fireworks competition.
-
D.
Ichigaya
Ichigaya is a central Tokyo district known for its major railway station, government and educational institutions, and proximity to the Imperial Palace area.
-
E.
Kamiyama
Kamiyama is a Japanese surname borne by various individuals, including artists, athletes, and public figures.
- 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_69d7bdf084148190ab9d513dc0735af4 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96208fa6481909d6fd43654752a2d |
completed | April 10, 2026, 8:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a012ec19c508190912c3fe186f8a992 |
completed | May 11, 2026, 1:20 a.m. |
| NEDg | Description generation | batch_6a01313d46908190a8e6df35a4bcf7e8 |
completed | May 11, 2026, 1:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a013198d2d08190b593694809ac2ad6 |
completed | May 11, 2026, 1:32 a.m. |
Created at: April 9, 2026, 5:23 p.m.