Triple
T4222738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | World Forestry Center |
E94379
|
entity |
| Predicate | DiscoveryMuseumFocus |
P18644
|
FINISHED |
| Object | forests and forestry around the world |
—
|
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: forests and forestry around the world | Statement: [World Forestry Center, DiscoveryMuseumFocus, forests and forestry around the world]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: DiscoveryMuseumFocus Context triple: [World Forestry Center, DiscoveryMuseumFocus, forests and forestry around the world]
-
A.
museumFocus
chosen
Indicates that a museum is primarily dedicated to or specializes in a particular subject, theme, or type of collection.
-
B.
purposeOfMuseum
Indicates that a specified purpose or function is attributed to a particular museum.
-
C.
museumAt
Indicates that an entity (such as an exhibit, artifact, or event) is located at or associated with a particular museum.
-
D.
museumCity
Indicates the city in which a given museum is located.
-
E.
majorMuseum
Indicates that a museum holds significant importance or prominence, typically due to its size, collections, reputation, or cultural impact.
- 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_69b3451997e08190851db4a9a588837d |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b34e4bf6088190926b982039a12079 |
completed | March 12, 2026, 11:37 p.m. |
| PD | Predicate disambiguation | batch_69b347f1d7b48190bd8974c03c7dc937 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:04 p.m.