Triple
T19741548
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kay County |
E474133
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Blackwell |
—
|
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: Blackwell | Statement: [Kay County, hasCity, Blackwell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blackwell Context triple: [Kay County, hasCity, Blackwell]
-
A.
Blackwell
Blackwell is a surname of English origin borne by numerous notable individuals across fields such as music, politics, and academia.
-
B.
Blackwell
Blackwell is a prominent academic publishing company known for producing scholarly books and journals across a wide range of disciplines.
-
C.
Blackwell
chosen
Blackwell is a small city in northern Oklahoma known historically for its agricultural roots and former zinc smelting industry.
-
D.
Harcout
Harcourt is a small rural town in central Victoria, Australia, known historically for its apple orchards and granite quarries.
-
E.
Bloomsbury
Bloomsbury is a central London district renowned for its literary heritage, academic institutions, and garden squares.
- 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_69d8e517ebd48190979ee76723bcfadf |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65162382081909bd5a251d7da7f75 |
completed | April 20, 2026, 4:16 p.m. |
Created at: April 10, 2026, 1:47 p.m.