Triple
T7879234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tema Industrial Area |
E182934
|
entity |
| Predicate | languageUsed |
P238
|
FINISHED |
| Object | Akan |
E54191
|
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: Akan | Statement: [Tema Industrial Area, languageUsed, Akan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Akan Context triple: [Tema Industrial Area, languageUsed, Akan]
-
A.
Akan
chosen
Akan is a major Central Tano language spoken primarily in Ghana and parts of Côte d’Ivoire, serving as a key lingua franca and cultural language for the Akan people.
-
B.
Anawan
Anawan was a Wampanoag war leader who became prominent during King Philip’s War as a key Native American commander against English colonial forces.
-
C.
Asaka
Asaka is a Japanese noble family name historically associated with a collateral branch of the Imperial Family, including Prince Asaka Yasuhiko.
-
D.
Kouaku
Kouaku is one of the small islands that make up the remote Gambier Islands archipelago in French Polynesia.
-
E.
Yasu
Yasu is a Japanese city located in Shiga Prefecture, known for its blend of residential areas, local industry, and proximity to Lake Biwa.
- 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_69ca828a17248190b46defe758bc5ad3 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb39be7ab88190affcd353a0cd37fa |
completed | March 31, 2026, 3:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5b86c20081909aa029cda7c48d44 |
completed | March 31, 2026, 5:28 a.m. |
Created at: March 30, 2026, 4:57 p.m.