Triple
T6992354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bijagós Archipelago |
E162114
|
entity |
| Predicate | containsIsland |
P970
|
FINISHED |
| Object | Orango |
E635522
|
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: Orango | Statement: [Bijagós Archipelago, containsIsland, Orango]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Orango Context triple: [Bijagós Archipelago, containsIsland, Orango]
-
A.
Orango
chosen
Orango is the principal and most extensive island of Guinea-Bissau’s Bijagós Archipelago, known for its rich biodiversity and traditional Bijagó communities.
-
B.
Dongo
Dongo is a small town on the northwestern shore of Lake Como in Lombardy, Italy, known for its role in the capture of Benito Mussolini at the end of World War II.
-
C.
Machar
Machar is a small rural township in Ontario, Canada, known for its forests, lakes, and low-density residential and agricultural character.
-
D.
Kabuna
Kabuna is a small village located on the atoll of Tabiteuea in the island nation of Kiribati in the central Pacific Ocean.
-
E.
Enyeama
Enyeama is a Nigerian surname most prominently associated with Vincent Enyeama, a renowned former goalkeeper and captain of the Nigeria national football team.
- 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_69c68856d7808190ab33ee914640281b |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dbc1f63c8190837cfd71cf5ed613 |
completed | March 27, 2026, 7:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c77551f85881909893d67176ee5556 |
completed | March 28, 2026, 6:29 a.m. |
Created at: March 27, 2026, 2:32 p.m.