Triple
T23259980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wendy |
E581976
|
entity |
| Predicate | firstMajorLiteraryUseDate |
P151577
|
FINISHED |
| Object | early 20th century |
—
|
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: early 20th century | Statement: [Wendy, firstMajorLiteraryUseDate, early 20th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstMajorLiteraryUseDate Context triple: [Wendy, firstMajorLiteraryUseDate, early 20th century]
-
A.
firstProminentUse
Indicates the earliest notable or widely recognized instance in which something was used in a significant or influential way.
-
B.
firstMajorLiteraryAppearanceAuthor
Indicates the author responsible for the work in which an entity made its first major literary appearance.
-
C.
firstHistoricalUse
Indicates that the subject entity represents the earliest known or recorded instance of the object entity being used or occurring in history.
-
D.
firstUseAsTitleDate
Indicates the date on which something was first used as a title.
-
E.
firstMajorUseYear
Indicates the calendar year in which something was first put into major or primary use.
- F. None of above. chosen
Provenance (4 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_69e246079f58819085eaa9c260906880 |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f194c7ec148190b01fd215a0c1daa1 |
completed | April 29, 2026, 5:19 a.m. |
| PD | Predicate disambiguation | batch_69effce4d704819092826931d430e8c4 |
completed | April 28, 2026, 12:18 a.m. |
| PDg | Predicate description generation | batch_69f01d8770d081908897c28b04e5faea |
completed | April 28, 2026, 2:37 a.m. |
Created at: April 17, 2026, 4:11 p.m.