Triple
T14845511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ambo |
E349074
|
entity |
| Predicate | nearbySettlement |
P350
|
FINISHED |
| Object | Bikenibeu |
E349070
|
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: Bikenibeu | Statement: [Ambo, nearbySettlement, Bikenibeu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bikenibeu Context triple: [Ambo, nearbySettlement, Bikenibeu]
-
A.
Bikenibeu
chosen
Bikenibeu is a major village and administrative center on Tarawa Atoll in the Pacific island nation of Kiribati.
-
B.
Bikenibeu Paeniu
Bikenibeu Paeniu is a Tuvaluan politician who served multiple terms as the country's prime minister during the 1990s.
-
C.
Bikel
Bikel is a surname most notably associated with Theodore Bikel, an Austrian-American actor, folk singer, and civil rights activist.
-
D.
Bikfaya
Bikfaya is a historic mountain town in Lebanon known for its cool climate, pine forests, and traditional Lebanese architecture.
-
E.
Biegun
Biegun is a Polish surname borne by various individuals, including figures in politics, academia, and the arts.
- 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_69d822ec69008190a9232caa68836872 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded291103c8190a64cfe700bfee197 |
completed | April 14, 2026, 11:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe72a87dd88190b0f0c3b9b625a7e6 |
completed | May 8, 2026, 11:32 p.m. |
Created at: April 10, 2026, 1:53 a.m.