Triple
T1980808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northern Borders Region |
E43020
|
entity |
| Predicate | hasCapital |
P204
|
FINISHED |
| Object | Arar |
E196368
|
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: Arar | Statement: [Northern Borders Region, hasCapital, Arar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arar Context triple: [Northern Borders Region, hasCapital, Arar]
-
A.
Arar
chosen
Arar is a city in northern Saudi Arabia that serves as the capital of the Northern Borders Region and a regional center for trade and administration.
-
B.
Nahe
Nahe is a renowned German wine region, particularly celebrated for producing high-quality Riesling wines with diverse styles due to its varied soils and microclimates.
-
C.
Rissne
Rissne is a residential district and urban area in the Stockholm metropolitan region of Sweden, known for its mix of apartment housing and proximity to public transit.
-
D.
Kawa
Kawa is a programming language framework that compiles Scheme and other high-level languages to Java bytecode for execution on the Java Virtual Machine.
-
E.
Kura
Kura is a major river in the South Caucasus that flows through Turkey, Georgia, and Azerbaijan before emptying into the Caspian Sea.
- 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_69a88713ddc88190a969715658ebe7a8 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb7c87bc081908ed179d1ca94fa3b |
completed | March 7, 2026, 5:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae0ad2a3888190a93e54b53a071afc |
completed | March 8, 2026, 11:48 p.m. |
Created at: March 4, 2026, 7:37 p.m.