Triple
T17093265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southeastern Guinea |
E414776
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Guinée forestière |
E784222
|
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: Guinée forestière | Statement: [Southeastern Guinea, partOf, Guinée forestière]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Guinée forestière Context triple: [Southeastern Guinea, partOf, Guinée forestière]
-
A.
Guinea
Guinea is a West African country on the Atlantic coast known for its rich mineral resources, diverse ethnic groups, and role as a major producer of bauxite.
-
B.
Gaboni
Gaboni is a small locality in southern Poland situated near the Beskid Sądecki mountain range, serving as a starting point for hikes to nearby peaks such as Przehyba.
-
C.
La Guinea
La Guinea is a small settlement located on Isla del Rey in Spain’s Balearic Islands.
-
D.
Guinea Forestière
chosen
Guinea Forestière is a heavily forested, resource-rich region in southeastern Guinea known for its biodiversity and ethnolinguistic diversity.
-
E.
Côte d'Ivoire
Côte d'Ivoire is a West African country on the Gulf of Guinea known for its cocoa production, diverse cultures, and economic prominence in the region.
- 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_69d886cfc8e88190b05ba466edd35591 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbfb89348190942984037bd3bd2e |
completed | April 18, 2026, 7:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a015fbe1d4c81909ce7e4626516b51d |
completed | May 11, 2026, 4:49 a.m. |
Created at: April 10, 2026, 5:35 a.m.