Triple
T33464874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joe Gargery |
E857017
|
entity |
| Predicate | appearsInSerializedFormIn |
P62614
|
FINISHED |
| Object | All the Year Round |
—
|
NE NERFINISHED |
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: All the Year Round | Statement: [Joe Gargery, appearsInSerializedFormIn, All the Year Round]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appearsInSerializedFormIn Context triple: [Joe Gargery, appearsInSerializedFormIn, All the Year Round]
-
A.
serializedIn
chosen
Indicates that something is published or presented in sequential installments within a larger medium or series.
-
B.
isSerializableIn
Indicates that something can be converted into a specific format or representation suitable for storage or transmission within a given context or system.
-
C.
originallySerialized
Indicates that one entity was first stored, recorded, or encoded in a serialized form by another entity or process.
-
D.
firstSerialisedIn
Indicates the original publication or medium in which something (such as a work or story) was first released in serialized form.
-
E.
hasSerialization
Indicates that one entity is represented, encoded, or stored as a serialized form in another entity.
- 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_69f34973461481909c701c98ebd75623 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fd884cb2b48190b6acd473430d9e19 |
completed | May 8, 2026, 6:53 a.m. |
| PD | Predicate disambiguation | batch_69fd8709ca208190a8bab836f0156af5 |
completed | May 8, 2026, 6:47 a.m. |
Created at: May 1, 2026, 1:37 a.m.