Triple
T11502594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Special Area of Conservation (in parts) |
E272698
|
entity |
| Predicate | threatsAddressedInclude |
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: [Special Area of Conservation (in parts), threatsAddressedInclude, habitat loss]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: threatsAddressedInclude Context triple: [Special Area of Conservation (in parts), threatsAddressedInclude, 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.
threatsManaged
Indicates that one entity takes responsibility for identifying, controlling, or mitigating risks or dangers affecting another entity or system.
-
C.
hasThreats
Indicates that one entity poses or is associated with potential danger, harm, or adverse consequences toward another entity.
-
D.
recognizesThreat
Indicates that an entity identifies or acknowledges another entity or situation as a potential danger or source of harm.
-
E.
countermeasuresFaced
Indicates that one entity has encountered or had to deal with countermeasures implemented by another entity.
- 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_69d6aae2c3748190bed2ea50dfb160dc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d85de55cbc8190be71c2d03dc044f2 |
completed | April 10, 2026, 2:18 a.m. |
| PD | Predicate disambiguation | batch_69d808736c5c8190899b5b3b2e797f65 |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:36 p.m.