Triple
T5456794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Machrie Moor stone circles |
E122497
|
entity |
| Predicate | numberOfStoneCircles |
P64152
|
FINISHED |
| Object | at least six |
—
|
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: at least six | Statement: [Machrie Moor stone circles, numberOfStoneCircles, at least six]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfStoneCircles Context triple: [Machrie Moor stone circles, numberOfStoneCircles, at least six]
-
A.
distanceToStonehenge
Indicates the measured or calculated spatial distance between a given entity and the location of Stonehenge.
-
B.
numberOfIndividualGeoglyphsApprox
Indicates an approximate count of distinct individual geoglyphs associated with a given subject.
-
C.
numberOfArchaeologicalSites
Indicates the total count of archaeological sites associated with a given entity or context.
-
D.
numberOfStelae
Indicates the quantity of stelae associated with a given entity or context.
-
E.
numberOfHeadstones
Indicates the total count of headstones associated with a given entity or location.
- F. None of above. chosen
Provenance (4 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_69bd46424248819085282ddf50a565f3 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd927c946c8190aef40679199fede3 |
completed | March 20, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69bd91a0d96c8190bd1299edbf764bbb |
completed | March 20, 2026, 6:27 p.m. |
| PDg | Predicate description generation | batch_69bd927b0b4c81909d5e0f594822e3f9 |
completed | March 20, 2026, 6:31 p.m. |
Created at: March 20, 2026, 2:08 p.m.