Triple
T9443458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tyne Cot Cemetery |
E227704
|
entity |
| Predicate | hasNumberOfUnidentifiedBurials |
P55820
|
FINISHED |
| Object | about 3500 |
—
|
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: about 3500 | Statement: [Tyne Cot Cemetery, hasNumberOfUnidentifiedBurials, about 3500]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfUnidentifiedBurials Context triple: [Tyne Cot Cemetery, hasNumberOfUnidentifiedBurials, about 3500]
-
A.
numberOfUnidentifiedBurials
chosen
Indicates the count of burial sites or graves where the interred individuals have not been identified.
-
B.
numberOfBurials
Indicates the total count of burial events associated with a given entity.
-
C.
numberOfUnidentifiedRemains
Indicates the count of human remains that have not yet been identified in a given context or case.
-
D.
hasBurialsOf
Indicates that a location or site contains or includes the burial places of certain individuals or groups.
-
E.
hasNotableBurials
Indicates that a place, typically a cemetery or burial site, contains the graves or remains of individuals considered notable or significant.
- 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_69ca843884488190ad6cbe0153088234 |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7f3171248190b92ab990371e63f5 |
completed | April 1, 2026, 8:25 p.m. |
| PD | Predicate disambiguation | batch_69cca5596ffc819097e9c8eefd4ef9b8 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:51 p.m.