Triple
T20102209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sanananda |
E496572
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Buna |
—
|
NE NERFINISHED |
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: Buna | Statement: [Sanananda, locatedNear, Buna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Buna Context triple: [Sanananda, locatedNear, Buna]
-
A.
Buna
Buna is the Nazi concentration and labor camp complex near Auschwitz where Elie Wiesel is imprisoned in his memoir "Night."
-
B.
Buna
chosen
Buna is a coastal village in Papua New Guinea that was a key site of intense fighting between Allied and Japanese forces during World War II’s New Guinea campaign.
-
C.
Buna
Buna is a short but significant karst river in Bosnia and Herzegovina, renowned for its powerful spring at Blagaj and its contribution to the Neretva river system.
-
D.
Bun
Bun is a modern, high-performance JavaScript runtime and toolkit designed as an alternative to Node.js and Deno, featuring a built-in bundler, test runner, and package manager.
-
E.
Busaiteen
Busaiteen is a coastal town in the Kingdom of Bahrain, located on Muharraq Island and known for its residential neighborhoods and proximity to Bahrain International Airport.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da626eee3881909f3454986d4a6511 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66670a5b48190afe06c8a582bba3d |
completed | April 20, 2026, 5:46 p.m. |
Created at: April 11, 2026, 11:27 p.m.