Triple
T25478687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Essex Farm Cemetery |
E638504
|
entity |
| Predicate | nearbyUnit |
P61362
|
FINISHED |
| Object | Canadian Field Artillery |
—
|
NE NERFINISHED |
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: Canadian Field Artillery | Statement: [Essex Farm Cemetery, nearbyUnit, Canadian Field Artillery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyUnit Context triple: [Essex Farm Cemetery, nearbyUnit, Canadian Field Artillery]
-
A.
nearbyTo
chosen
Indicates that one entity is located close in distance or position to another entity.
-
B.
nearbyLocation
Indicates that one location is situated close to another location in physical space.
-
C.
nearbyUNPresence
Indicates that there is a United Nations presence located in close physical proximity to the referenced entity or location.
-
D.
nearbyCurrent
Indicates that one entity is located close to another entity at the present moment or in the current context.
-
E.
hasNearbySquare
Indicates that one entity has at least one square-shaped entity located close to it in space.
- 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_69e75db9b964819096802dcf502e577e |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f676c440708190a4b9974e95d2291a |
completed | May 2, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69f675fd59608190b246383435e68fce |
completed | May 2, 2026, 10:09 p.m. |
Created at: April 21, 2026, 2:27 p.m.