Triple
T21860677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Louvetier de France |
E539751
|
entity |
| Predicate | typeOfHuntingConcerned |
P87170
|
FINISHED |
| Object | wolf hunting |
—
|
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: wolf hunting | Statement: [Grand Louvetier de France, typeOfHuntingConcerned, wolf hunting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfHuntingConcerned Context triple: [Grand Louvetier de France, typeOfHuntingConcerned, wolf hunting]
-
A.
hasWildlifeIssue
Indicates that an entity is affected by, involved in, or responsible for a problem or conflict related to wildlife.
-
B.
isHuntedBy
Indicates that one entity is the target of hunting activity carried out by another entity.
-
C.
hasConservationConcernIn
Indicates that an entity is subject to a specified conservation concern status within a particular geographic area or jurisdiction.
-
D.
associatedWithHunting
chosen
Indicates a relationship where an entity is connected to, involved in, or commonly linked with the activity or practice of hunting.
-
E.
hunting
Indicates one entity actively pursuing and attempting to capture or kill another entity, typically as prey.
- 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_69e0c47829648190bbe2d1d7033768ec |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f0d63a22b88190b59b13e7b4788195 |
completed | April 28, 2026, 3:46 p.m. |
| PD | Predicate disambiguation | batch_69e6be9394f88190945ddd1dc004d29d |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 6:56 p.m.