Triple
T358459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Argosy |
E7596
|
entity |
| Predicate | firstIssueFormat |
P130
|
FINISHED |
| Object | children's weekly story paper |
—
|
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: children's weekly story paper | Statement: [Argosy, firstIssueFormat, children's weekly story paper]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstIssueFormat Context triple: [Argosy, firstIssueFormat, children's weekly story paper]
-
A.
firstRaisedAt
Indicates the initial time or context at which an issue, topic, or matter was first brought up or introduced.
-
B.
firstAppeared
Indicates the earliest known time or context in which an entity was introduced, observed, or came into existence.
-
C.
firstUsedFor
Indicates that one entity was the earliest or original thing for which another entity was used or applied.
-
D.
firstRaisedBy
Indicates that one entity was the earliest or original source to bring up, introduce, or initiate the referenced issue, idea, or topic in relation to another entity.
-
E.
format
chosen
Indicates the specific arrangement, structure, or presentation style in which something is organized or expressed.
- 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_69a2e7e696948190bebc966535995e45 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebb0e348819086e3ccd96c7b129e |
completed | Feb. 28, 2026, 1:20 p.m. |
| PD | Predicate disambiguation | batch_69a2e959ce948190a201c017eecb7c95 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.