Triple
T23341207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hal Blaine |
E591737
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Blaine |
—
|
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: Blaine | Statement: [Hal Blaine, familyName, Blaine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blaine Context triple: [Hal Blaine, familyName, Blaine]
-
A.
Blaine
Blaine is a small coastal city in northwestern Washington State, located near the Canadian border.
-
B.
Blaine
chosen
Blaine is a surname most notably associated with James G. Blaine, a prominent 19th-century American statesman and politician.
-
C.
Blaine
Blaine is the laid-back, surfing-obsessed teenage protagonist of the 1993 comedy film "Airborne," known for his inline skating skills and culture clash after moving from California to Cincinnati.
-
D.
Blaine
Blaine is a thoughtful African American academic and love interest in Chimamanda Ngozi Adichie’s novel "Americanah," representing a particular strand of Black American intellectual and political life.
-
E.
Leland
Leland is a masculine given name of English origin, historically associated with figures such as American industrialist and Stanford University founder Leland Stanford.
- 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_69e25d20e3d08190bcede87673cafb25 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f198329d9c8190992627afa9b54bed |
completed | April 29, 2026, 5:33 a.m. |
Created at: April 17, 2026, 5:18 p.m.