Triple
T16826296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | T. M. Aluko |
E409026
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object |
Ijero-Ekiti
Ijero-Ekiti is a town in Ekiti State, southwestern Nigeria, known as a traditional Yoruba community and local government headquarters.
|
E1235080
|
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: Ijero-Ekiti | Statement: [T. M. Aluko, placeOfBirth, Ijero-Ekiti]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ijero-Ekiti Context triple: [T. M. Aluko, placeOfBirth, Ijero-Ekiti]
-
A.
Oye-Ekiti
Oye-Ekiti is a town in Ekiti State, southwestern Nigeria, known as an educational hub and administrative center in the region.
-
B.
Ijebu-Igbo
Ijebu-Igbo is a prominent town in Ogun State, southwestern Nigeria, historically significant as a cultural and economic center of the Ijebu people.
-
C.
Ijebu Ijesa
Ijebu Ijesa is a prominent town in Osun State, southwestern Nigeria, historically associated with the Ijesha people and known as a local commercial and cultural center.
-
D.
Ibarapa region
The Ibarapa region is a predominantly agrarian area in southwestern Nigeria, known for its Yoruba communities and towns such as Eruwa.
-
E.
Ondo
Ondo is a historic Yoruba town in southwestern Nigeria known for its traditional monarchy, cultural heritage, and role as a regional commercial center.
- 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: Ijero-Ekiti Triple: [T. M. Aluko, placeOfBirth, Ijero-Ekiti]
Generated description
Ijero-Ekiti is a town in Ekiti State, southwestern Nigeria, known as a traditional Yoruba community and local government headquarters.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ijero-Ekiti Target entity description: Ijero-Ekiti is a town in Ekiti State, southwestern Nigeria, known as a traditional Yoruba community and local government headquarters.
-
A.
Oye-Ekiti
Oye-Ekiti is a town in Ekiti State, southwestern Nigeria, known as an educational hub and administrative center in the region.
-
B.
Ijebu-Igbo
Ijebu-Igbo is a prominent town in Ogun State, southwestern Nigeria, historically significant as a cultural and economic center of the Ijebu people.
-
C.
Ijebu Ijesa
Ijebu Ijesa is a prominent town in Osun State, southwestern Nigeria, historically associated with the Ijesha people and known as a local commercial and cultural center.
-
D.
Ibarapa region
The Ibarapa region is a predominantly agrarian area in southwestern Nigeria, known for its Yoruba communities and towns such as Eruwa.
-
E.
Ondo
Ondo is a historic Yoruba town in southwestern Nigeria known for its traditional monarchy, cultural heritage, and role as a regional commercial center.
- 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_69d88394566c8190b3dcbdc72935f7fa |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b31404c88190a3b2802842ca77eb |
completed | April 18, 2026, 4:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00b29e48f881908489bd77a9caec97 |
completed | May 10, 2026, 4:30 p.m. |
| NEDg | Description generation | batch_6a00b3aafac08190b3e0181780f45392 |
completed | May 10, 2026, 4:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00b466ecd08190b7b5ee54476631ab |
completed | May 10, 2026, 4:37 p.m. |
Created at: April 10, 2026, 5:23 a.m.