Triple
T18375457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Town |
E446301
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Townes |
—
|
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: Townes | Statement: [Town, hasVariant, Townes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Townes Context triple: [Town, hasVariant, Townes]
-
A.
Townes
chosen
Townes is the surname of Charles Hard Townes, the American physicist and Nobel laureate known for his pioneering work on the maser and laser.
-
B.
Delmore
Delmore is a masculine given name most notably associated with the American poet and short story writer Delmore Schwartz.
-
C.
Justin Townes Earle
Justin Townes Earle was an American singer-songwriter known for his blend of Americana, folk, and country music and for being part of a prominent musical family.
-
D.
Charlotte Belt
The Charlotte Belt is a geologic terrane in the southeastern United States characterized by metamorphic and igneous rocks that help define the region’s complex tectonic history.
-
E.
Tharpe
Tharpe is a surname, often a variant of "Tharp," associated with several notable individuals in fields such as music and sports.
- 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_69d8b9f370b88190b1e5081c2c238e7f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e51759353481908aa2de599fd2cf3b |
completed | April 19, 2026, 5:56 p.m. |
Created at: April 10, 2026, 10:45 a.m.