Triple
T23849726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Daughters of Erietown |
E592125
|
entity |
| Predicate | debutStatus |
P124335
|
FINISHED |
| Object | first novel by Connie Schultz |
—
|
LITERAL FINISHED |
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: first novel by Connie Schultz | Statement: [The Daughters of Erietown, debutStatus, first novel by Connie Schultz]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: debutStatus Context triple: [The Daughters of Erietown, debutStatus, first novel by Connie Schultz]
-
A.
debutAs
Indicates that an entity makes its first public appearance or introduction in a particular role, medium, or context.
-
B.
debutResult
Indicates the outcome or performance result associated with an entity’s first formal appearance or introduction (its debut).
-
C.
debuted
Indicates that an entity made its first public appearance, performance, or introduction at a particular time or place.
-
D.
hasDebutStatusForAuthor
chosen
Indicates that an author’s work or appearance is identified as their first (debut) instance in a given context.
-
E.
isDebut
Indicates that something is the first formal appearance or introduction of an entity, such as a person, work, or performance, in a particular context or domain.
- F. None of above.
Provenance (3 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_69e25d221d908190b9b502ad31e66a3f |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c986f7e08190a6d361423946ff05 |
completed | April 29, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_69f1614612b481908c45d99e588882f9 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:11 p.m.