Triple
T26706250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zenaida macroura |
E673293
|
entity |
| Predicate | huntingStatus |
P132704
|
FINISHED |
| Object | heavily hunted in parts of North America |
—
|
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: heavily hunted in parts of North America | Statement: [Zenaida macroura, huntingStatus, heavily hunted in parts of North America]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: huntingStatus Context triple: [Zenaida macroura, huntingStatus, heavily hunted in parts of North America]
-
A.
hasHuntingActivity
Indicates that an entity engages in, performs, or is involved in hunting-related activities.
-
B.
huntingTime
Indicates the time period during which a hunting activity takes place or is scheduled.
-
C.
hunting
Indicates one entity actively pursuing and attempting to capture or kill another entity, typically as prey.
-
D.
huntingStyle
Indicates the characteristic manner or method an entity typically uses when hunting.
-
E.
isHuntedBy
chosen
Indicates that one entity is the target of hunting activity carried out 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_69eecda2b49c8190a6c481cfc4c07954 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f617b9d9648190a1f50ece0815b857 |
completed | May 2, 2026, 3:26 p.m. |
| PD | Predicate disambiguation | batch_69f60b8dfa0c8190864e1a940024d0a0 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 27, 2026, 3:34 a.m.