Triple
T14615435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Braun |
E343072
|
entity |
| Predicate | hasNotableBearerCount |
P107844
|
FINISHED |
| Object | multiple |
—
|
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 | Statement: [Thomas Braun, hasNotableBearerCount, multiple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableBearerCount Context triple: [Thomas Braun, hasNotableBearerCount, multiple]
-
A.
hasNotableBearersCount
chosen
Indicates the number of notable individuals or entities that bear or are associated with the subject.
-
B.
hasNotableBearer
Indicates that an entity (such as a name, title, or identifier) is borne by at least one notable person or entity.
-
C.
hasNotableBearersType
Indicates that an entity has notable bearers belonging to a specified type or category.
-
D.
hasNotableBearerForm
Indicates that a particular form or variant of something is notably associated with a specific bearer or holder.
-
E.
hasNotableBearerOrdinalNumber
Indicates that an entity is associated with a notable bearer identified by a specific ordinal position (e.g., first, second, third) among others with the same name or 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_69d822dec68081908c2553145c4051dc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb45264988190a1df13e8b54a85bd |
completed | April 14, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69de656f9f4c81909f815b6629a9ee39 |
completed | April 14, 2026, 4:03 p.m. |
Created at: April 10, 2026, 1:25 a.m.