Triple
T190483
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lower Egypt |
E3708
|
entity |
| Predicate | hasAdministrativeDivision |
P747
|
FINISHED |
| Object | nomes |
—
|
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: nomes | Statement: [Lower Egypt, hasAdministrativeDivision, nomes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdministrativeDivision Context triple: [Lower Egypt, hasAdministrativeDivision, nomes]
-
A.
hasAdministrativeCenter
Indicates that an administrative unit (such as a region, district, or municipality) has a specific place designated as its main governing or administrative center.
-
B.
hasSubdivision
chosen
Indicates that one entity is divided into and contains another entity as one of its constituent parts or administrative units.
-
C.
hasCivilDivision
Indicates that one administrative or political entity is subdivided into, or is associated with, a specific civil division (such as a county, district, or municipality).
-
D.
countrySubdivision
Indicates that one geopolitical region is an administrative or territorial subdivision of a larger country.
-
E.
hasNumberOfProvinces
Indicates the total count of provinces associated with a given entity.
- 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_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a2594c385481909e1e088e45c460a4 |
completed | Feb. 28, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69a25673ce3c8190b1a3df5b814a0595 |
completed | Feb. 28, 2026, 2:44 a.m. |
Created at: Feb. 28, 2026, 2:41 a.m.