Triple
T2223177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hickory Hill Park |
E48186
|
entity |
| Predicate | hasWildlifeType |
P22447
|
FINISHED |
| Object | songbirds |
—
|
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: songbirds | Statement: [Hickory Hill Park, hasWildlifeType, songbirds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWildlifeType Context triple: [Hickory Hill Park, hasWildlifeType, songbirds]
-
A.
hasNearbyWildlife
Indicates that there is wildlife located close to or in the immediate vicinity of the referenced entity.
-
B.
hasAnimal
Indicates that one entity possesses, keeps, or is associated with an animal.
-
C.
hasBirdSpecies
Indicates that there exists a relationship in which a subject possesses, contains, or is associated with a particular bird species.
-
D.
hasWildPopulationOf
Indicates that a location or area contains a naturally occurring, non-captive population of the specified species.
-
E.
hasBiodiversityFeature
chosen
Indicates that an entity possesses or is associated with a specific biodiversity-related characteristic, attribute, or element.
- 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_69a88aa1ee708190862c8c378c41e9eb |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc03d1df88190950c691a4c246bd1 |
completed | March 7, 2026, 6:05 a.m. |
| PD | Predicate disambiguation | batch_69abbdac31d8819092d17815e11921e9 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.