Triple
T6722611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Gers |
E153431
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | The Teddy Bears |
E153433
|
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: The Teddy Bears | Statement: [The Gers, alsoKnownAs, The Teddy Bears]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Teddy Bears Context triple: [The Gers, alsoKnownAs, The Teddy Bears]
-
A.
Teddy Bears
chosen
Teddy Bears is a popular nickname for Rangers F.C., one of Scotland’s most successful and widely supported football clubs.
-
B.
Boo-Boo Bear
Boo-Boo Bear is a gentle, bow-tie-wearing cartoon bear best known as Yogi Bear’s loyal sidekick in the classic Hanna-Barbera animated series.
-
C.
Cubbie Bear
Cubbie Bear is the costumed bear mascot of the Iowa Cubs minor league baseball team, entertaining fans at games and community events.
-
D.
Teddy
Teddy is Mr. Bean’s beloved brown teddy bear, a silent yet expressive companion that often serves as his confidant and playmate in the comedy series.
-
E.
Teddy
Teddy is a character in Louisa May Alcott’s novel "Jo’s Boys," part of the continuation of the March family saga begun in "Little Women."
- 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_69c6880afb988190ad88011b48ecfcba |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d139d50c81908b19120f139deaa5 |
completed | March 27, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c700a14ebc819092cc40f522540f1a |
completed | March 27, 2026, 10:11 p.m. |
Created at: March 27, 2026, 2:08 p.m.