Triple
T801451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Upper Egypt |
E17135
|
entity |
| Predicate | predominantSettlementType |
P1830
|
FINISHED |
| Object | rural |
—
|
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: rural | Statement: [Upper Egypt, predominantSettlementType, rural]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: predominantSettlementType Context triple: [Upper Egypt, predominantSettlementType, rural]
-
A.
humanSettlementType
Indicates the classification of a human settlement based on its form or function, such as village, town, or city.
-
B.
mainSettlement
Indicates that one settlement serves as the primary or most important settlement associated with a given area, region, or administrative unit.
-
C.
hasPopulationCenterType
Indicates the classification of a population center by its type, such as city, town, village, or other settlement category.
-
D.
hadPrimarySettlementPattern
chosen
Indicates that an entity exhibited or was characterized by a particular dominant form or arrangement of human settlement.
-
E.
urbanAreaType
Indicates the classification of an area based on its urban characteristics or development type (e.g., city, town, suburb, metropolitan region).
- 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_69a49378b9c48190adbf5f62e5b7aca1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a7cc75e88190bd35aabe51051b51 |
completed | March 1, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69a4a5133bf88190a613e96d1f7cffa7 |
completed | March 1, 2026, 8:44 p.m. |
Created at: March 1, 2026, 7:38 p.m.