Triple
T31738536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iberian wolf |
E810069
|
entity |
| Predicate | protectedStatusInSpain |
P55090
|
FINISHED |
| Object | varies by region and national protections |
—
|
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: varies by region and national protections | Statement: [Iberian wolf, protectedStatusInSpain, varies by region and national protections]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: protectedStatusInSpain Context triple: [Iberian wolf, protectedStatusInSpain, varies by region and national protections]
-
A.
statusInSpain
chosen
Indicates the legal, social, or official condition or standing that an entity has within the jurisdiction of Spain.
-
B.
legalStatusWithinCastile
Indicates the legal standing or rights an entity holds under the laws and jurisdiction specific to Castile.
-
C.
certificationSpain
Indicates that an entity holds or is associated with a certification that is valid, issued, or recognized in Spain.
-
D.
legalStatusInPortugal
Indicates the legal status or classification that an entity holds specifically within the jurisdiction of Portugal.
-
E.
statusInMexico
Indicates the legal or social status that an entity holds within the context of Mexico.
- 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_69f348e0e4908190a884582eca646fb7 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6d74b20a48190900dda1014cc13a8 |
completed | May 3, 2026, 5:04 a.m. |
| PD | Predicate disambiguation | batch_69f6d26f27dc8190ae426a3e1573933e |
completed | May 3, 2026, 4:43 a.m. |
Created at: April 30, 2026, 11:24 p.m.