Triple
T30818356
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | القسطلاني |
E784845
|
entity |
| Predicate | الانتماء_الجغرافي |
P3227
|
FINISHED |
| Object | من علماء مصر |
—
|
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: من علماء مصر | Statement: [القسطلاني, الانتماء_الجغرافي, من علماء مصر]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: الانتماء_الجغرافي Context triple: [القسطلاني, الانتماء_الجغرافي, من علماء مصر]
-
A.
geographicContext
chosen
Indicates that one entity is situated within, associated with, or characterized by the geographic setting or region defined by another entity.
-
B.
geopoliticalRegion
Indicates a relationship where an entity is a defined political or administrative geographic area, such as a country, state, province, or similar region.
-
C.
geographicDivision
Indicates that one place is an administrative or territorial subdivision of another place.
-
D.
isPoliticalGeographicUnit
Indicates that an entity functions as a defined geographic area used for political or administrative purposes, such as governance, representation, or jurisdiction.
-
E.
geographicalRegionType
Indicates the specific kind or category of geographical region that an entity belongs to (e.g., continent, country, province, or city).
- 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_69f224b4eda48190bd212ce4f3901e56 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f697eabb048190bc01a830f14942c6 |
completed | May 3, 2026, 12:33 a.m. |
| PD | Predicate disambiguation | batch_69f69664142c8190bc695501056b0236 |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 29, 2026, 8:44 p.m.