Triple
T29302401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenuzi |
E742992
|
entity |
| Predicate | regionOfUseAlong |
P908
|
FINISHED |
| Object | Nile River valley in southern Egypt |
—
|
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: Nile River valley in southern Egypt | Statement: [Kenuzi, regionOfUseAlong, Nile River valley in southern Egypt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionOfUseAlong Context triple: [Kenuzi, regionOfUseAlong, Nile River valley in southern Egypt]
-
A.
usedInRegion
chosen
Indicates that something is utilized or applied within a specific geographic or administrative region.
-
B.
regionFrom
Indicates that something originates from, is derived from, or is associated with a particular geographic or administrative region.
-
C.
locatedAlong
Indicates that one entity is situated adjacent to, or running beside, the length or course of another linear feature (such as a road, river, or railway).
-
D.
usedRegion
Indicates that an entity operates in, applies to, or is utilized within a specified geographic or administrative region.
-
E.
regionNameUsedFor
Indicates that a particular region name is used to refer to or designate a specific region or area.
- F. None of above.
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_69f09123ed9881909f351f7541933f5e |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69fd68abf52881909c5a390c362b7c59 |
completed | May 8, 2026, 4:38 a.m. |
| PD | Predicate disambiguation | batch_69fd6812d0c88190930d8fa2d4b92490 |
completed | May 8, 2026, 4:35 a.m. |
Created at: April 28, 2026, 1:10 p.m.