Triple
T312260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Riyadh |
E7632
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object | Najd |
E44274
|
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: Najd | Statement: [Riyadh, region, Najd]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Najd Context triple: [Riyadh, region, Najd]
-
A.
Najd
chosen
Najd is the central plateau region of Saudi Arabia, historically known as a heartland of Arab tribal culture and the birthplace of the modern Saudi state.
-
B.
Nain
Nain is a remote coastal town in northern Labrador, Canada, known as the administrative center of the Inuit region of Nunatsiavut.
-
C.
Kadmat
Kadmat is a coral island in India’s Lakshadweep archipelago, known for its white-sand beaches, clear lagoons, and vibrant marine life that make it a popular destination for snorkeling and diving.
-
D.
Kamen
Kamen is a surname most prominently associated with American inventor and entrepreneur Dean Kamen, known for creating the Segway and numerous medical devices.
-
E.
Gori
Gori is a city in central Georgia best known as the birthplace of Soviet leader Joseph Stalin.
- 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_69a2e7e7af7881908890039d6be4e9b8 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ea4aa16881909b2c8404b85992df |
completed | Feb. 28, 2026, 1:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3dd2c45e881908f4508bcf9d7cae2 |
completed | March 1, 2026, 6:31 a.m. |
Created at: Feb. 28, 2026, 1:07 p.m.