Triple
T14373996
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Characters Edition Winston Churchill |
E356426
|
entity |
| Predicate | hasNibType |
P74466
|
FINISHED |
| Object | fountain pen nib |
—
|
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: fountain pen nib | Statement: [Great Characters Edition Winston Churchill, hasNibType, fountain pen nib]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNibType Context triple: [Great Characters Edition Winston Churchill, hasNibType, fountain pen nib]
-
A.
haveType
Indicates that an entity belongs to or is classified under a specified type or category.
-
B.
hasNodeType
Indicates that an entity is associated with, or classified as, a specific type of node within a structured system or model.
-
C.
hasBondType
Indicates the specific kind of bond or connection that exists between two related entities.
-
D.
hasJointType
Indicates that one entity is associated with, or characterized by, a specific type or category of joint.
-
E.
hasAccessoryType
chosen
Indicates that an entity is associated with or characterized by a particular type or category of accessory.
- 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_69d8279163a081908aec45c0e3f1e02f |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de9007184c8190aebb003cb6548cc8 |
completed | April 14, 2026, 7:05 p.m. |
| PD | Predicate disambiguation | batch_69de2a9cb3e081909f6b33fdd939bb9e |
completed | April 14, 2026, 11:53 a.m. |
Created at: April 10, 2026, 1:15 a.m.