Triple
T7072453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tim the Bear’s neighborhood |
E164731
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Stoolbend |
E31720
|
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: Stoolbend | Statement: [Tim the Bear’s neighborhood, partOf, Stoolbend]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stoolbend Context triple: [Tim the Bear’s neighborhood, partOf, Stoolbend]
-
A.
Stoolbend
chosen
Stoolbend is the fictional Virginia town that serves as the primary setting for the animated television series "The Cleveland Show."
-
B.
The Butts
"The Butts" is a poem by Carl Dennis included in his collection "Human Chain," reflecting his characteristic meditative and narrative style.
-
C.
Toilet Tisha
"Toilet Tisha" is a song by the hip-hop duo OutKast from their acclaimed 2000 album *Stankonia*.
-
D.
Gulpen
Gulpen is a village in the hilly Limburg region of the Netherlands, known for its scenic landscapes, historic center, and local brewery culture.
-
E.
Binetto
Binetto is a small town and comune in the Apulia region of southern Italy, situated within the Metropolitan City of Bari.
- 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_69c6887b96548190a8a9b3ac8adf4119 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e4c9cdbc8190b91cd3b4eef58eb6 |
completed | March 27, 2026, 8:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7945fdafc81909c265373627af4e8 |
completed | March 28, 2026, 8:42 a.m. |
Created at: March 27, 2026, 2:39 p.m.