Triple
T9364995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canadian National Vimy Memorial |
E225376
|
entity |
| Predicate | siteFeatures |
P80690
|
FINISHED |
| Object | preserved trench lines |
—
|
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: preserved trench lines | Statement: [Canadian National Vimy Memorial, siteFeatures, preserved trench lines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: siteFeatures Context triple: [Canadian National Vimy Memorial, siteFeatures, preserved trench lines]
-
A.
featuresIn
chosen
Indicates that an entity appears or plays a role within another entity, such as a person or element being included in a work, event, or context.
-
B.
featuresSuit
Indicates that one entity includes or presents a particular suit (e.g., clothing, armor, or outfit) as a notable component or attribute.
-
C.
featuresService
Indicates that one entity provides, includes, or offers a particular service as a notable characteristic or component.
-
D.
featuresInstitution
Indicates that one entity includes, presents, or highlights an institution as a notable component or participant.
-
E.
featuresText
Indicates that an entity includes or presents a specific piece of text as one of its characteristics or contents.
- 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_69ca842cbddc819099d71ecec48cf9e5 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd503fd7f081909655e2a880c84834 |
completed | April 1, 2026, 5:05 p.m. |
| PD | Predicate disambiguation | batch_69cc7a6abb8c81908c7a2f4ee92cc949 |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:43 p.m.