Triple
T20533127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Userkaf |
E504119
|
entity |
| Predicate | praenomenTransliteration |
P33650
|
FINISHED |
| Object | Wsr-k3.f |
—
|
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: Wsr-k3.f | Statement: [Userkaf, praenomenTransliteration, Wsr-k3.f]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wsr-k3.f Context triple: [Userkaf, praenomenTransliteration, Wsr-k3.f]
-
A.
Wsr-kꜢ.f
chosen
Wsr-kꜢ.f is the praenomen (throne name) of the ancient Egyptian pharaoh Userkaf, the first king of the Fifth Dynasty of the Old Kingdom.
-
B.
WS3
WS3 is a postal district within the WS postcode area in the West Midlands region of England, covering parts of Walsall and its surrounding localities.
-
C.
KWS
KWS is the government agency responsible for conserving and managing Kenya’s wildlife and protected areas.
-
D.
K3
K3 is another name for Broad Peak, a major mountain in the Karakoram range and one of the world’s fourteen peaks over 8,000 meters.
-
E.
K3
K3 is a three-valued logical system introduced by Stephen Kleene that extends classical logic with an additional truth value to handle partial or undefined information.
- 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_69e0b4b3a6e08190ae663701f50fab8e |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a06d30508190a13d1a9855b441fb |
completed | April 20, 2026, 9:53 p.m. |
Created at: April 16, 2026, 11:37 a.m.