Triple
T5765087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | nꜥr-mr |
E127191
|
entity |
| Predicate | kingNumber |
P3023
|
FINISHED |
| Object | first king of the 1st Dynasty of Egypt (traditional attribution) |
—
|
LITERAL 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: first king of the 1st Dynasty of Egypt (traditional attribution) | Statement: [nꜥr-mr, kingNumber, first king of the 1st Dynasty of Egypt (traditional attribution)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: kingNumber Context triple: [nꜥr-mr, kingNumber, first king of the 1st Dynasty of Egypt (traditional attribution)]
-
A.
numberOfKings
Indicates the quantity of entities that hold the role or title of king in a given context.
-
B.
kingOf
Indicates that one entity holds the position or role of king in relation to another entity, typically a territory, people, or domain.
-
C.
monarchNumber
chosen
Indicates the ordinal position or sequence number assigned to a monarch within a line of rulers.
-
D.
queenLength
Indicates the length or duration associated with a queen in the given context.
-
E.
alsoKingOf
Indicates that an entity who is king of one place is simultaneously king of another place as well.
- 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_69c00834f6308190851b0abeddd8ed7e |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02acb12c081908e4beee4a957f9f9 |
completed | March 22, 2026, 5:45 p.m. |
| PD | Predicate disambiguation | batch_69c021ce8d3c81909b332cb1c33a61ad |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:49 p.m.