Triple
T19853111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | No Morning After |
E477053
|
entity |
| Predicate | hasAuthorSurname |
P97092
|
FINISHED |
| Object | Clarke |
—
|
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: Clarke | Statement: [No Morning After, hasAuthorSurname, Clarke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Clarke Context triple: [No Morning After, hasAuthorSurname, Clarke]
-
A.
Clarke
chosen
Clarke is a common English and Irish surname historically associated with the occupation of a clerk or scholar.
-
B.
Dartnell
Dartnell is a surname most notably associated with Jorge Chávez Dartnell, a pioneering early 20th-century Peruvian aviator.
-
C.
Hadley
Hadley is a given name most notably borne by Hadley Richardson, the first wife of writer Ernest Hemingway.
-
D.
Clerke
Clerke is a surname of English origin borne by various notable individuals, including British naval officer and explorer Charles Clerke.
-
E.
Lander
Lander is a surname most notably associated with Frederick W. Lander, a 19th-century American civil engineer, explorer, and Union Army general.
- 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_69d8e51d39d081909bcfafeaaf3d2fcc |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65869e1b481908e2a2a2074ff4a6d |
completed | April 20, 2026, 4:46 p.m. |
Created at: April 10, 2026, 1:51 p.m.