Triple
T6269115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Branch Brook Park |
E140484
|
entity |
| Predicate | speciesOfCherryTrees |
P59038
|
FINISHED |
| Object | more than a dozen varieties |
—
|
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: more than a dozen varieties | Statement: [Branch Brook Park, speciesOfCherryTrees, more than a dozen varieties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: speciesOfCherryTrees Context triple: [Branch Brook Park, speciesOfCherryTrees, more than a dozen varieties]
-
A.
hasTrees
Indicates that something possesses or contains one or more trees.
-
B.
notableVarieties
chosen
Indicates that there are specific, distinguished types or versions associated with an entity that are recognized as notable.
-
C.
isInlandVarietyOf
Indicates that one entity is a variety or subtype of another that occurs specifically in inland (non-coastal) areas.
-
D.
notableTreeSpecies
Indicates that the subject place or area is known for, or characterized by, the specified tree species.
-
E.
numberOfTrees
Indicates the count or quantity of trees associated with a given entity or context.
- 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_69c008cabc4081909723e2547c9d6cc0 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c063a28da081909f4bec8f7c1dedef |
completed | March 22, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69c05606fb50819082d1a5a91e5030b6 |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:25 p.m.