Triple
T3077315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lagos State |
E64168
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Ikeja GRA |
E131789
|
NE FINISHED |
How this triple was built (2 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: Ikeja GRA | Statement: [Lagos State, hasCity, Ikeja GRA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ikeja GRA Context triple: [Lagos State, hasCity, Ikeja GRA]
-
A.
Ikeja
chosen
Ikeja is a major commercial and administrative hub in Nigeria, serving as the capital of Lagos State and hosting numerous businesses, government offices, and the Murtala Muhammed International Airport.
-
B.
Toyonaka
Toyonaka is a suburban city in Japan’s Kansai region known for its residential neighborhoods, educational institutions, and proximity to central Osaka.
-
C.
Suginami
Suginami is a residential ward in western Tokyo, Japan, known for its quiet neighborhoods, anime studios, and vibrant local shopping streets.
-
D.
Toshima
Toshima is a special ward in northwest Tokyo known for the major commercial and entertainment hub of Ikebukuro and its dense urban residential districts.
-
E.
Setagaya
Setagaya is a large residential ward in western Tokyo, Japan, known for its suburban neighborhoods, parks, and role as a commuter area for central Tokyo.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ad857a8aec8190bfdfd9c14554ac5a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada1a6f6148190ae5cd6e45eda9006 |
completed | March 8, 2026, 4:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1f88d32a08190b4e18da4b26b534c |
completed | March 11, 2026, 11:19 p.m. |
Created at: March 8, 2026, 3:02 p.m.