Triple
T4411263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anatidae |
E94857
|
entity |
| Predicate | containsSpecies |
P7733
|
FINISHED |
| Object | whooper swan |
E280999
|
NE 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: whooper swan | Statement: [Anatidae, containsSpecies, whooper swan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: whooper swan Context triple: [Anatidae, containsSpecies, whooper swan]
-
A.
Swan
Swan is a small city in Marion County, Iowa, United States.
-
B.
Swan
chosen
Swan is a large, graceful waterbird known for its long neck, white or black plumage, and strong cultural associations with beauty and elegance.
-
C.
Loon
Loon is a historic medieval county in what is now eastern Belgium, centered around the city of Borgloon and influential in the region’s feudal politics.
-
D.
Loon
Loon was an experimental Alphabet project that aimed to provide internet connectivity to remote and underserved regions using high-altitude balloons.
-
E.
Ouack the duckling
Ouack the duckling is one of the fictional duckling characters from Robert McCloskey’s classic children’s book "Make Way for Ducklings."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69b34539638c8190abfea3eb29425210 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b354e656dc819093ca8395d7334006 |
completed | March 13, 2026, 12:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5f6131de08190968259a0be73cd3f |
completed | March 14, 2026, 11:58 p.m. |
Created at: March 12, 2026, 11:29 p.m.