Triple
T26707597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | chimney swift |
E673321
|
entity |
| Predicate | winteringCountry |
P19711
|
FINISHED |
| Object | Ecuador |
—
|
NE NERFINISHED |
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: Ecuador | Statement: [chimney swift, winteringCountry, Ecuador]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winteringCountry Context triple: [chimney swift, winteringCountry, Ecuador]
-
A.
winteringAreas
Indicates the locations where entities spend the winter season, typically as their non-breeding or overwintering grounds.
-
B.
wintersIn
chosen
Indicates that an entity spends the winter season in a particular place or region.
-
C.
fallCountry
Indicates that an entity collapses, fails, or loses control within the context of a specified country.
-
D.
winterTouristSeason
Indicates that the relationship or context occurs during the winter period when tourism activity is at its peak or is specifically targeted.
-
E.
winterCharacteristic
Indicates a characteristic, feature, or quality that is specifically associated with or typical of winter.
- 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_69eecda3a22881908f3061c760b9d542 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f61a17a7788190946f7e32d63cd43f |
completed | May 2, 2026, 3:36 p.m. |
| PD | Predicate disambiguation | batch_69f611ab768c8190b1849c15a3e59dda |
completed | May 2, 2026, 3 p.m. |
Created at: April 27, 2026, 3:34 a.m.