Triple
T24069309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Twentysix Gasoline Stations |
E596180
|
entity |
| Predicate | thirdEditionPrintRun |
P29899
|
FINISHED |
| Object | 3000 copies |
—
|
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: 3000 copies | Statement: [Twentysix Gasoline Stations, thirdEditionPrintRun, 3000 copies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thirdEditionPrintRun Context triple: [Twentysix Gasoline Stations, thirdEditionPrintRun, 3000 copies]
-
A.
thirdEditionPublicationDate
Indicates the date on which the third edition of a work was published.
-
B.
numberOfItemsInThirdEdition
chosen
Indicates the quantity of items contained in the third edition of a given work or collection.
-
C.
thirdEditionYears
Indicates the years during which the third edition of something (e.g., a work, event, or product) was in effect, published, or took place.
-
D.
firstEditionPrintRun
Indicates the initial quantity of copies produced when a work is printed in its first published edition.
-
E.
thirdSeriesPublicationYear
Indicates the year in which the third installment of a series was 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_69e288c25c008190850cf447940ab181 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1db15866c8190ab931216b8d9c57f |
completed | April 29, 2026, 10:19 a.m. |
| PD | Predicate disambiguation | batch_69f1764b1d4c8190b12590c6339c31c1 |
completed | April 29, 2026, 3:08 a.m. |
Created at: April 17, 2026, 10:41 p.m.