Triple
T17093287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kissi |
E414777
|
entity |
| Predicate | spokenIn |
P2266
|
FINISHED |
| Object | Guinea |
E40812
|
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: Guinea | Statement: [Kissi, spokenIn, Guinea]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Guinea Context triple: [Kissi, spokenIn, Guinea]
-
A.
Guinea
chosen
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.
La Guinea
La Guinea is a small settlement located on Isla del Rey in Spain’s Balearic Islands.
-
C.
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.
-
D.
Gabon
Gabon is a Central African country on the Atlantic coast, known for its equatorial rainforests, rich biodiversity, and significant oil reserves.
-
E.
The Gambia
The Gambia is a small West African country centered around the Gambia River, known for its diverse ecosystems, colonial history, and tourism-focused economy.
- 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_6a0141422d6c819086dc98988c0851d9 |
completed | May 11, 2026, 2:38 a.m. |
Created at: April 10, 2026, 5:35 a.m.