Triple
T62170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | golden eagle |
E1234
|
entity |
| Predicate | primaryThreats |
P1006
|
FINISHED |
| Object | habitat loss |
—
|
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: habitat loss | Statement: [golden eagle, primaryThreats, habitat loss]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryThreats Context triple: [golden eagle, primaryThreats, habitat loss]
-
A.
threatenedBy
Indicates that one entity poses a danger or potential harm to another entity.
-
B.
hazardType
Indicates the specific kind or category of hazard associated with an entity or situation.
-
C.
primaryEcosystem
Indicates the main type of ecosystem in which an entity predominantly exists or operates.
-
D.
conservationIssue
Indicates that an entity is associated with a problem, threat, or concern related to the protection, preservation, or sustainable management of natural resources or biodiversity.
-
E.
environmentalIssue
chosen
Indicates that something is a problem or concern related to the natural environment, such as harm, risk, or negative impact on ecosystems or resources.
- 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_69a24ba4f760819081f6638a3c70538a |
completed | Feb. 28, 2026, 1:57 a.m. |
| NER | Named-entity recognition | batch_69a251f74b0881909ad89127b8171277 |
completed | Feb. 28, 2026, 2:24 a.m. |
| PD | Predicate disambiguation | batch_69a24ea242c8819086fe00bf01e6523e |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:02 a.m.