Triple
T35338612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Francisco Oracle |
E1020532
|
entity |
| Predicate | circaNumberOfIssues |
P31088
|
FINISHED |
| Object | around 12 issues |
—
|
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: around 12 issues | Statement: [San Francisco Oracle, circaNumberOfIssues, around 12 issues]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: circaNumberOfIssues Context triple: [San Francisco Oracle, circaNumberOfIssues, around 12 issues]
-
A.
mainSeriesIssueCount
Indicates the total number of issues contained in the primary or main series associated with an entity.
-
B.
numberOfIssues
chosen
Indicates the quantity of issues associated with a given entity or context.
-
C.
pageCountPerIssue
Indicates the number of pages contained in each individual issue of a recurring publication.
-
D.
circulationPeriod
Indicates the length of time during which an item is allowed to be borrowed, used, or remain in active circulation before it must be returned, renewed, or retired.
-
E.
yearOfFirstIssue
Indicates the calendar year in which something (such as a publication, document, or item) was first issued or released.
- 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_69f76debb4e08190be52d89b8af2392d |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f79533b88c8190934ec4cb21770e24 |
completed | May 3, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69f79104f5b48190a496cdffde8472da |
completed | May 3, 2026, 6:16 p.m. |
Created at: May 3, 2026, 4:03 p.m.