Triple
T12712199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ado-Odo/Ota |
E303746
|
entity |
| Predicate | hasMajorTown |
P316
|
FINISHED |
| Object |
Igbesa
Igbesa is a prominent town in Ogun State, Nigeria, known for its growing industrial presence and educational institutions.
|
E1027235
|
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: Igbesa | Statement: [Ado-Odo/Ota, hasMajorTown, Igbesa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Igbesa Context triple: [Ado-Odo/Ota, hasMajorTown, Igbesa]
-
A.
Nkwerre
Nkwerre is a town and local government area in southeastern Nigeria known for its location within Imo State and its cultural and commercial activities.
-
B.
Ogwashi-Ukwu
Ogwashi-Ukwu is a town in Delta State, southern Nigeria, known as the hometown of prominent economist and World Trade Organization Director-General Ngozi Okonjo-Iweala.
-
C.
Isi-Uzo
Isi-Uzo is a local government area in southeastern Nigeria known for its predominantly rural communities and cultural ties to the larger Enugu region.
-
D.
Mmahu-Egbema
Mmahu-Egbema is a town in Imo State, southeastern Nigeria, serving as the administrative center of the Ohaji/Egbema Local Government Area.
-
E.
Ikposo
Ikposo is a Niger-Congo language spoken primarily by the Akposso people in Togo and parts of neighboring West African countries.
- 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: Igbesa Triple: [Ado-Odo/Ota, hasMajorTown, Igbesa]
Generated description
Igbesa is a prominent town in Ogun State, Nigeria, known for its growing industrial presence and educational institutions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Igbesa Target entity description: Igbesa is a prominent town in Ogun State, Nigeria, known for its growing industrial presence and educational institutions.
-
A.
Nkwerre
Nkwerre is a town and local government area in southeastern Nigeria known for its location within Imo State and its cultural and commercial activities.
-
B.
Ogwashi-Ukwu
Ogwashi-Ukwu is a town in Delta State, southern Nigeria, known as the hometown of prominent economist and World Trade Organization Director-General Ngozi Okonjo-Iweala.
-
C.
Isi-Uzo
Isi-Uzo is a local government area in southeastern Nigeria known for its predominantly rural communities and cultural ties to the larger Enugu region.
-
D.
Mmahu-Egbema
Mmahu-Egbema is a town in Imo State, southeastern Nigeria, serving as the administrative center of the Ohaji/Egbema Local Government Area.
-
E.
Ikposo
Ikposo is a Niger-Congo language spoken primarily by the Akposso people in Togo and parts of neighboring West African countries.
- 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_69f6f5b9e0c4819095194dc42677e17f |
completed | May 3, 2026, 7:14 a.m. |
| NEDg | Description generation | batch_69f6f80b420c8190b5028be4fa99fb59 |
completed | May 3, 2026, 7:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6f89072a88190b3182f581b1b6762 |
completed | May 3, 2026, 7:26 a.m. |
Created at: April 9, 2026, 5:23 p.m.