Triple
T38675368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canadian War Memorials Fund |
E943723
|
entity |
| Predicate | numberOfArtistsCommissioned |
P201560
|
FINISHED |
| Object | over 100 |
—
|
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: over 100 | Statement: [Canadian War Memorials Fund, numberOfArtistsCommissioned, over 100]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfArtistsCommissioned Context triple: [Canadian War Memorials Fund, numberOfArtistsCommissioned, over 100]
-
A.
hasCommissionedComposersCount
Indicates the number of composers that an entity has commissioned to create works.
-
B.
representedArtists
Indicates that one entity (typically an agent, gallery, or organization) serves as the professional representative for another entity (typically an artist) in managing or promoting their work.
-
C.
approximateNumberOfArtistsAndCrafters
chosen
Indicates an estimated count of individuals who are artists or crafters involved in a given context or event.
-
D.
numberOfGuestArtists
Indicates the count of guest artists associated with or participating in a particular work, event, or entity.
-
E.
numberOfPaintingsCreated
Indicates the total count of paintings that an entity has created.
- 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_69f76eec28708190b9c82a505fc278e0 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a2026248190b894436a578d79ac |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:33 p.m.