Triple
T31644801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liddle Burnt Mound |
E807554
|
entity |
| Predicate | isTypeExampleOf |
P103345
|
FINISHED |
| Object | Orkney burnt mounds |
—
|
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: Orkney burnt mounds | Statement: [Liddle Burnt Mound, isTypeExampleOf, Orkney burnt mounds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isTypeExampleOf Context triple: [Liddle Burnt Mound, isTypeExampleOf, Orkney burnt mounds]
-
A.
isModelOf
Indicates that one entity serves as a representation or abstraction that captures the structure or behavior of another entity.
-
B.
isPartOfType
Indicates that one type or category is a constituent or subset within a larger, encompassing type or category.
-
C.
instanceOf
relation of type constraints
-
D.
hasExampleType
chosen
Indicates that something is associated with a specific type or category of example that characterizes or illustrates it.
-
E.
sonInstanceOf
Indicates that an entity is a specific instance or example of the general concept or class represented by "son."
- 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_69f348d9ce58819093ea2da83cbeeec1 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a91e4f4c8190831089d81f5f0026 |
completed | May 3, 2026, 1:47 a.m. |
| PD | Predicate disambiguation | batch_69f6a757c6e081908e37631e5d8d246b |
completed | May 3, 2026, 1:39 a.m. |
Created at: April 30, 2026, 10:50 p.m.