Triple
T35186758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Patty (Peanuts) |
E1016004
|
entity |
| Predicate | firstAppearanceRelative |
P100688
|
FINISHED |
| Object | appeared in the earliest years of Peanuts |
—
|
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: appeared in the earliest years of Peanuts | Statement: [Patty (Peanuts), firstAppearanceRelative, appeared in the earliest years of Peanuts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstAppearanceRelative Context triple: [Patty (Peanuts), firstAppearanceRelative, appeared in the earliest years of Peanuts]
-
A.
firstAppearanceFor
Indicates that an entity marks the initial occurrence or debut of another entity within a given context or medium.
-
B.
firstAppearanceApprox
chosen
Indicates that one entity is the approximate or estimated first appearance of another entity in time or context.
-
C.
firstAppeared
Indicates the earliest known time or context in which an entity was introduced, observed, or came into existence.
-
D.
firstAppearanceAct
Indicates the act in which an entity makes its first appearance within a work or performance.
-
E.
settingOfFirstAppearance
Indicates the location or context in which an entity is first introduced or appears.
- 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_69f76ddd815c8190b822eea06630f9fb |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a016960819093ed4990fb4d9d36 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:02 p.m.