Triple
T12712156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abeokuta North |
E303745
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Iberekodo
Iberekodo is a locality within Abeokuta North in Ogun State, southwestern Nigeria.
|
E996868
|
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: Iberekodo | Statement: [Abeokuta North, hasSettlement, Iberekodo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Iberekodo Context triple: [Abeokuta North, hasSettlement, Iberekodo]
-
A.
Getxo
Getxo is a coastal town in the Basque Country of northern Spain, known for its beaches, historic neighborhoods, and proximity to Bilbao.
-
B.
Plentzia
Plentzia is a coastal town and popular beachside resort in the province of Biscay in Spain’s Basque Country.
-
C.
Zabaltegi
Zabaltegi is a non-competitive, open-themed section of the San Sebastián International Film Festival that showcases a diverse selection of innovative and noteworthy films.
-
D.
Hondarribia
Hondarribia is a historic coastal town in Spain’s Basque Country, known for its well-preserved old quarter, fishing port, and location on the border with France.
-
E.
Bilbao
Bilbao is a major port city in northern Spain renowned for its industrial heritage, cultural institutions like the Guggenheim Museum, and role as an economic hub of the Basque Country.
- 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: Iberekodo Triple: [Abeokuta North, hasSettlement, Iberekodo]
Generated description
Iberekodo is a locality within Abeokuta North in Ogun State, southwestern Nigeria.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Iberekodo Target entity description: Iberekodo is a locality within Abeokuta North in Ogun State, southwestern Nigeria.
-
A.
Getxo
Getxo is a coastal town in the Basque Country of northern Spain, known for its beaches, historic neighborhoods, and proximity to Bilbao.
-
B.
Plentzia
Plentzia is a coastal town and popular beachside resort in the province of Biscay in Spain’s Basque Country.
-
C.
Zabaltegi
Zabaltegi is a non-competitive, open-themed section of the San Sebastián International Film Festival that showcases a diverse selection of innovative and noteworthy films.
-
D.
Hondarribia
Hondarribia is a historic coastal town in Spain’s Basque Country, known for its well-preserved old quarter, fishing port, and location on the border with France.
-
E.
Bilbao
Bilbao is a major port city in northern Spain renowned for its industrial heritage, cultural institutions like the Guggenheim Museum, and role as an economic hub of the Basque Country.
- 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_69f671b8f43081909d4a8e4241c813a1 |
completed | May 2, 2026, 9:50 p.m. |
| NEDg | Description generation | batch_69f672ac07908190bd2dfe90d55a13c1 |
completed | May 2, 2026, 9:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f67360b530819085d5db2aa0b7513d |
completed | May 2, 2026, 9:57 p.m. |
Created at: April 9, 2026, 5:23 p.m.