Triple
T36567092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calidris mauri |
E902006
|
entity |
| Predicate | migrationStopoverSites |
P43131
|
FINISHED |
| Object | Pacific coast estuaries |
—
|
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: Pacific coast estuaries | Statement: [Calidris mauri, migrationStopoverSites, Pacific coast estuaries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: migrationStopoverSites Context triple: [Calidris mauri, migrationStopoverSites, Pacific coast estuaries]
-
A.
isStopoverSiteFor
Indicates that a location serves as a temporary stopping or resting point along the route or journey of another entity.
-
B.
stopoverLocation
Indicates that an entity makes an intermediate stop or layover at a specified location during a journey or route.
-
C.
isStopoverPoint
Indicates that a location serves as an intermediate stopping point along a journey or route, rather than the final destination.
-
D.
trailStopOn
Indicates that one entity stops or terminates at the endpoint of a trail or path associated with another entity.
-
E.
typicalStopoverRegion
chosen
Indicates the geographic region where an entity (such as a migrating animal or traveler) most commonly makes an intermediate stop during its journey.
- 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_69f76e6416708190a9754b8c52d4e453 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c777e924819081a6634f549fe552 |
completed | May 3, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69f7c477a4d481908f52e55b6688f60c |
completed | May 3, 2026, 9:56 p.m. |
Created at: May 3, 2026, 4:11 p.m.