Triple
T19243370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SAFE (Saving Animals From Extinction) |
E481185
|
entity |
| Predicate | typeOfThreatsAddressed |
P19863
|
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: [SAFE (Saving Animals From Extinction), typeOfThreatsAddressed, habitat loss]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfThreatsAddressed Context triple: [SAFE (Saving Animals From Extinction), typeOfThreatsAddressed, habitat loss]
-
A.
threatTypeAddressed
chosen
Indicates that a given action, measure, or entity is specifically intended to counter or mitigate a particular type of threat.
-
B.
typeOfSecurityAddressed
Indicates the category or kind of security concern, risk, or protection that is being addressed in a given context.
-
C.
featuresThreat
Indicates that one entity includes, presents, or contains a threat associated with another entity.
-
D.
hasThreats
Indicates that one entity poses or is associated with potential danger, harm, or adverse consequences toward another entity.
-
E.
recognizesThreat
Indicates that an entity identifies or acknowledges another entity or situation as a potential danger or source of harm.
- 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_69d8e8cd9d1081908a181d02b88b59b8 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5faf3018881909ef866616c45ff2e |
completed | April 20, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e4dd002d00819088b625056edfb74e |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:27 p.m.