Triple
T3003865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Longdon |
E81850
|
entity |
| Predicate | hasWarCemeteries |
P36715
|
FINISHED |
| Object | British military graves |
—
|
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: British military graves | Statement: [Mount Longdon, hasWarCemeteries, British military graves]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWarCemeteries Context triple: [Mount Longdon, hasWarCemeteries, British military graves]
-
A.
hasBurialsFromConflict
chosen
Indicates that the subject location or site contains burials that originated as a result of a specific conflict or violent event.
-
B.
numberOfCemeteries
Indicates the count of cemeteries associated with a given entity or within a specified area.
-
C.
hasCemetery
Indicates that one entity possesses, contains, or includes a cemetery associated with it.
-
D.
hasNotableBurials
Indicates that a place, typically a cemetery or burial site, contains the graves or remains of individuals considered notable or significant.
-
E.
hasNearbyMilitaryHistorySite
Indicates that an entity is located close to a site of historical military significance, such as a battlefield, fort, or memorial.
- 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_69ad8b1c4de88190a83b7cefaa1f2842 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a149b248190ac4f11afc4871cc1 |
completed | March 8, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69ad96180eb08190a524c5f458d41382 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:59 p.m.