Triple
T11030090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boe |
E260733
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Gabu Region |
E899819
|
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: Gabu Region | Statement: [Boe, partOf, Gabu Region]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gabu Region Context triple: [Boe, partOf, Gabu Region]
-
A.
Gabu Region
chosen
Gabu Region is an administrative region in eastern Guinea-Bissau known for its savanna landscapes and diverse ethnic communities.
-
B.
Bago Region
Bago Region is an administrative division in central Myanmar known for its historical cities, agricultural economy, and role as a significant site of political unrest and protests.
-
C.
Hhohho Region
Hhohho Region is an administrative region in northern Eswatini that includes the national capital, Mbabane, and is known for its mountainous terrain.
-
D.
Dikhil Region
Dikhil Region is an administrative region in southwestern Djibouti known for its arid landscapes, border location near Ethiopia, and the town of Dikhil as its capital.
-
E.
Sila Region
Sila Region is an administrative region in eastern Chad known for its arid Sahelian landscape and proximity to the Sudanese border.
- 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_69d6aa979bdc8190bf0e79104cc098c1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797d2feb881909a5684721e8b0d9c |
completed | April 9, 2026, 12:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3a9a6db688190a740b787448d97b2 |
completed | April 18, 2026, 3:56 p.m. |
Created at: April 8, 2026, 9:25 p.m.