Triple
T19535581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Regional at Best |
E488758
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Trees |
—
|
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: Trees | Statement: [Regional at Best, hasPart, Trees]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trees Context triple: [Regional at Best, hasPart, Trees]
-
A.
Trees
chosen
Trees is a well-known live music venue in Dallas, Texas, recognized for hosting a wide range of rock, metal, and alternative acts in an intimate club setting.
-
B.
Tree
Tree is a common surname that has been borne by various individuals, including those in English-speaking countries.
-
C.
Tree Trunks
Tree Trunks is a small, elderly yellow elephant from the animated series "Adventure Time," known for her love of baking apple pies and her unexpectedly adventurous spirit.
-
D.
TREE
TREE is the stock ticker symbol for LendingTree, an online marketplace that connects consumers with multiple lenders for loans and other financial products.
-
E.
Treene
The Treene is a river in northern Germany that flows through the state of Schleswig-Holstein and ultimately drains into the Eider River.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8db5b6c8190984b61f91981f575 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6386ddc208190962195b8aa568bed |
completed | April 20, 2026, 2:30 p.m. |
Created at: April 10, 2026, 1:41 p.m.