Triple
T26138107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | منف |
E659435
|
entity |
| Predicate | كانت_ترتبط_إداريًا_ب |
P37165
|
FINISHED |
| Object | إقليم الجميز (الإقليم الأول من مصر السفلى) |
—
|
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: إقليم الجميز (الإقليم الأول من مصر السفلى) | Statement: [منف, كانت_ترتبط_إداريًا_ب, إقليم الجميز (الإقليم الأول من مصر السفلى)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: كانت_ترتبط_إداريًا_ب Context triple: [منف, كانت_ترتبط_إداريًا_ب, إقليم الجميز (الإقليم الأول من مصر السفلى)]
-
A.
associatedWithAdministration
chosen
Indicates a relationship in which an entity is connected to, involved in, or under the responsibility of an administrative body, process, or function.
-
B.
usedToRelate
Indicates that one entity previously had a relationship or association with another, but that relationship no longer holds in the present.
-
C.
relatedTo
Indicates a general, non-specific relationship or association exists between two entities.
-
D.
associatedWithManager
Indicates that an entity has a managerial connection or relationship with a specific manager.
-
E.
relatedToTerm
Indicates a general, non-specific relationship or association between one term and 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_69ee5bc3c20c8190bf2cf272f4170e95 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f63fd6c68481908c542aa03e297b9c |
completed | May 2, 2026, 6:17 p.m. |
| PD | Predicate disambiguation | batch_69f63c6456608190b94e7c2e2c2a4824 |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 26, 2026, 8:18 p.m.