Triple
T3077312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lagos State |
E64168
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Lekki |
E288149
|
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: Lekki | Statement: [Lagos State, hasCity, Lekki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lekki Context triple: [Lagos State, hasCity, Lekki]
-
A.
Lekki
Lekki is the official mascot character created for the XVIII Olympic Winter Games.
-
B.
Lekki
chosen
Lekki is a rapidly developing coastal city and affluent residential and commercial hub in Lagos State, Nigeria.
-
C.
Lekki
Lekki is a fictional companion mascot character associated with Nokki, likely designed as a cute, supportive sidekick figure.
-
D.
Eso Ikoyi
Eso Ikoyi were an elite warrior caste of the Oyo Empire in Yorubaland, renowned for their strict code of honor, bravery, and key role in the empire’s military campaigns.
-
E.
Harpurhey
Harpurhey is an inner-city district of Manchester, England, known for its dense residential areas and local shopping precincts.
- 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.