Triple
T2613853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duke of Norfolk |
E58838
|
entity |
| Predicate | titleNumberOfCreations |
P4419
|
FINISHED |
| Object | multiple historical creations |
—
|
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: multiple historical creations | Statement: [Duke of Norfolk, titleNumberOfCreations, multiple historical creations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleNumberOfCreations Context triple: [Duke of Norfolk, titleNumberOfCreations, multiple historical creations]
-
A.
titleCount
chosen
Indicates the number of distinct titles associated with an entity within a given context.
-
B.
numberOfWorksCreated
Indicates the total count of creative works that an entity has produced or authored.
-
C.
titleNumber
Indicates the numerical designation or sequence number assigned to a title within an ordered set of titles.
-
D.
numberOfPaintingsCreated
Indicates the total count of paintings that an entity has created.
-
E.
uniqueTitleHolderCount
Indicates the number of distinct entities that exclusively hold a given title, with no other entity sharing that same title.
- 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_69ab4ac444dc819099614e534dd6021f |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd89325308190985598373eb0d296 |
completed | March 7, 2026, 7:49 a.m. |
| PD | Predicate disambiguation | batch_69abd80cd7fc81909e9696db2919129f |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:50 p.m.