Triple
T13565739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jonglei |
E324029
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Bor |
E487049
|
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: Bor | Statement: [Jonglei, capital, Bor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bor Context triple: [Jonglei, capital, Bor]
-
A.
Bor
chosen
Bor is a major town in South Sudan’s Jonglei State, situated on the White Nile and serving as an important regional administrative and transport hub.
-
B.
Bor
Bor is a town in Nizhny Novgorod Oblast, Russia, located on the left bank of the Volga River opposite the city of Nizhny Novgorod and known for its industrial and river transport significance.
-
C.
Bor
Bor is a London Underground station serving the Borough area of Southwark in central London.
-
D.
Bor
Bor is a small town in the Plzeň Region of the Czech Republic, known for its historic architecture and surrounding rural landscape.
-
E.
Bori
Bori is a prominent urban center in Nigeria’s Rivers State, serving as an important commercial and administrative hub for the surrounding region.
- 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_69d8076830b48190910a902bae5888e2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb00cecd48190a9a2caff3d424817 |
completed | April 12, 2026, 2:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75daf1bfc8190bf22eb9ef242f54f |
completed | May 3, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:48 p.m.