Triple
T34711243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meretnebty |
E1000650
|
entity |
| Predicate | nameInEgyptologicalTransliteration |
P75698
|
FINISHED |
| Object | Mr.t-nb.tj |
—
|
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: Mr.t-nb.tj | Statement: [Meretnebty, nameInEgyptologicalTransliteration, Mr.t-nb.tj]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nameInEgyptologicalTransliteration Context triple: [Meretnebty, nameInEgyptologicalTransliteration, Mr.t-nb.tj]
-
A.
nameInHieroglyphs
Indicates that an entity’s name is written or represented using hieroglyphic script.
-
B.
ancientEgyptianName
Indicates that one entity is the ancient Egyptian name or designation historically used for the other entity.
-
C.
nameInPhoenician
Indicates the representation of an entity’s name when written in the Phoenician language or script.
-
D.
nameInManetho
Indicates that an entity is referred to by a particular name in the historical works attributed to Manetho.
-
E.
transliterationName
chosen
Indicates that one entity is the transliterated form of another entity’s name from one writing system into another.
- 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_69f76dad3f108190a280fd0a2f4ee89a |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f77ffa6b68819090257fed3802c239 |
completed | May 3, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69f7795978c481909e152cd1bd02dd07 |
completed | May 3, 2026, 4:35 p.m. |
Created at: May 3, 2026, 3:59 p.m.