Triple
T36580167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calidris |
E902368
|
entity |
| Predicate | typicalNonBreedingRegion |
P151286
|
FINISHED |
| Object | coastal areas on multiple continents |
—
|
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: coastal areas on multiple continents | Statement: [Calidris, typicalNonBreedingRegion, coastal areas on multiple continents]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalNonBreedingRegion Context triple: [Calidris, typicalNonBreedingRegion, coastal areas on multiple continents]
-
A.
typicalRegionType
Indicates that a region is of a characteristic or commonly occurring type for a given context or entity.
-
B.
nonBreedingRangeIncludes
chosen
Indicates that the specified geographic area is part of the region where the species occurs outside its breeding season.
-
C.
primaryBreedingRegions
Indicates the main geographic areas where a species typically breeds or reproduces.
-
D.
naturalRegionOf
Indicates that one entity is the natural geographic region or area in which the other entity is located or to which it belongs.
-
E.
typicalZones
Indicates that certain spatial or contextual areas are characteristic or commonly associated with a given entity or situation.
- 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_69f76e64d8908190868473959a250b94 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0bf4b88190bdcfae9a14b51f0a |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:11 p.m.