Triple
T5887084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flora Nwapa |
E130890
|
entity |
| Predicate | birthPlace |
P1
|
FINISHED |
| Object | Oguta |
E368591
|
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: Oguta | Statement: [Flora Nwapa, birthPlace, Oguta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oguta Context triple: [Flora Nwapa, birthPlace, Oguta]
-
A.
Oguta
chosen
Oguta is a town and local government area in southeastern Nigeria known for its scenic Oguta Lake and cultural significance within Imo State.
-
B.
Nakawa
Nakawa is one of the energetic human hosts in Disney’s “Festival of the Lion King” stage show at Disney’s Animal Kingdom.
-
C.
Izumiotsu
Izumiotsu is a coastal city in Osaka Prefecture, Japan, known for its port facilities and industrial waterfront along Osaka Bay.
-
D.
Oshino
Oshino is a small village in Japan’s Yamanashi Prefecture, known for its traditional rural scenery and the crystal-clear spring ponds of Oshino Hakkai fed by Mount Fuji’s snowmelt.
-
E.
Kukawa
Kukawa is a historic town in northeastern Nigeria that once served as the political and cultural center of the Kanuri people and the Bornu Empire.
- 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_69c0085628dc8190b334c1b44c067efc |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0367a61648190bf97746caa4061fe |
completed | March 22, 2026, 6:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6d4fa68c08190bb656aef231a9df0 |
completed | March 27, 2026, 7:05 p.m. |
Created at: March 22, 2026, 3:57 p.m.