Triple
T27163740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | She Came to Stay |
E682727
|
entity |
| Predicate | hasISBNOfEnglishEdition |
P20928
|
FINISHED |
| Object | 9780393318838 |
—
|
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: 9780393318838 | Statement: [She Came to Stay, hasISBNOfEnglishEdition, 9780393318838]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasISBNOfEnglishEdition Context triple: [She Came to Stay, hasISBNOfEnglishEdition, 9780393318838]
-
A.
hasEnglishEdition
Indicates that one entity has a version or edition of itself that is produced or available in the English language.
-
B.
isbnFirstEnglishEdition
chosen
Indicates that the object is the ISBN identifier corresponding to the first English-language edition of the subject work.
-
C.
hasAlternateEditionISBN
Indicates that one edition of a work is linked to another edition of the same work via its alternate ISBN.
-
D.
languageOfOfficialEditions
Indicates the language in which the official editions or versions of a work, document, or publication are produced or authorized.
-
E.
EnglishEditionPublicationYear
Indicates the calendar year in which the English-language edition of a work was first published.
- 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_69eefacf6e788190a75a64399d9e3109 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f65aa07c048190a5df30d53d8f0cf5 |
completed | May 2, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69f659cc571c819097e51e531961d812 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 27, 2026, 9:20 a.m.