Triple
T499794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qena |
E10374
|
entity |
| Predicate | regionalFunction |
P12921
|
FINISHED |
| Object | administrative hub for surrounding rural areas |
—
|
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: administrative hub for surrounding rural areas | Statement: [Qena, regionalFunction, administrative hub for surrounding rural areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionalFunction Context triple: [Qena, regionalFunction, administrative hub for surrounding rural areas]
-
A.
regionType
Indicates the classification or category of a region, specifying what kind of region it is (e.g., administrative, geographic, or functional).
-
B.
hasRegionalRole
chosen
Indicates that an entity holds a specific role, function, or responsibility within a defined geographic region.
-
C.
regionallyAssociatedWith
Indicates that two entities are connected or related based on sharing the same or overlapping geographic or regional context.
-
D.
regionName
Indicates the name assigned to a specific geographic or administrative region.
-
E.
regionSpecificContent
Indicates that certain content is tailored, restricted, or applicable only to a particular geographic region or set of regions.
- 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_69a2e847df8481909239ec08ccf1e376 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f13096248190a622a58dcf540b00 |
completed | Feb. 28, 2026, 1:44 p.m. |
| PD | Predicate disambiguation | batch_69a2edfa87cc8190a77c726a5a55b7d9 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.