Triple
T13506129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St Leonard’s Church ossuary |
E321018
|
entity |
| Predicate | estimatedNumberOfBones |
P87416
|
FINISHED |
| Object | several thousand |
—
|
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: several thousand | Statement: [St Leonard’s Church ossuary, estimatedNumberOfBones, several thousand]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedNumberOfBones Context triple: [St Leonard’s Church ossuary, estimatedNumberOfBones, several thousand]
-
A.
numberOfBonesRecovered
Indicates the count of bones that have been found and recovered in relation to a particular subject or event.
-
B.
limbCount
Indicates the number of limbs an entity possesses.
-
C.
hasBoneColor
Indicates that an entity possesses a bone whose color matches the specified value.
-
D.
skeletonCompleteness
Indicates the degree to which an entity’s skeleton is present, intact, or fully preserved in relation to its expected complete form.
-
E.
skeletonAbundance
chosen
Indicates the relative quantity or richness of skeletal remains present in or associated with an entity.
- 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_69d807629d6c8190998f1b9bb12d2ed0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaf8259a08190ada13c4a3078f07d |
completed | April 12, 2026, 2:43 p.m. |
| PD | Predicate disambiguation | batch_69dbae0b63748190b5e207f84b2532ea |
completed | April 12, 2026, 2:36 p.m. |
Created at: April 9, 2026, 9:43 p.m.