Triple
T4068086
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ascott |
E86376
|
entity |
| Predicate | ruralSettlement |
P36501
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Ascott, ruralSettlement, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ruralSettlement Context triple: [Ascott, ruralSettlement, true]
-
A.
traditionalSettlement
Indicates that an entity is a settlement characterized by long-established, customary, or historically rooted patterns of habitation and land use.
-
B.
isRuralSettlement
chosen
Indicates that a settlement is located in a rural area, typically characterized by low population density and limited urban infrastructure.
-
C.
typicalSettlement
Indicates that the subject is a common or characteristic type of settlement typically found in the context of the object.
-
D.
humanSettlementType
Indicates the classification of a human settlement based on its form or function, such as village, town, or city.
-
E.
mainSettlement
Indicates that one settlement serves as the primary or most important settlement associated with a given area, region, or administrative unit.
- 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_69aed93c69208190a4efac0efe3cd69b |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefbf8f33c8190a6afca1830f35485 |
completed | March 9, 2026, 4:57 p.m. |
| PD | Predicate disambiguation | batch_69aef9061d2481908307cafc9e9b32c0 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:38 p.m.