Triple
T14481120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Usermaatre Setepenre |
E359102
|
entity |
| Predicate | usedAsCartoucheName |
P114368
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Usermaatre Setepenre, usedAsCartoucheName, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedAsCartoucheName Context triple: [Usermaatre Setepenre, usedAsCartoucheName, yes]
-
A.
writtenWithCartouche
Indicates that the text or name is inscribed enclosed within a cartouche.
-
B.
charterName
Indicates the official name or title assigned in a charter that defines or authorizes an entity or arrangement.
-
C.
hasCharacterNamedAfter
Indicates that one entity has a character whose name is derived from or intentionally based on another entity.
-
D.
usesBrandCharacter
Indicates that one entity employs or features another entity’s brand character (such as a mascot or branded persona) in its materials, products, or communications.
-
E.
characterSetName
Indicates the name assigned to a particular character set used for encoding or representing characters.
- F. None of above. chosen
Provenance (4 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_69d827966698819082e140837737501d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de924bc548819087a2f693840d7426 |
completed | April 14, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69de5c487b4c819097803e58dca628a5 |
completed | April 14, 2026, 3:24 p.m. |
| PDg | Predicate description generation | batch_69de5fb4de14819092acdecbd201d672 |
completed | April 14, 2026, 3:39 p.m. |
Created at: April 10, 2026, 1:20 a.m.