Triple
T29924597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Boyd |
E760042
|
entity |
| Predicate | nameHasMultipleBearers |
P168267
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Robert Boyd, nameHasMultipleBearers, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nameHasMultipleBearers Context triple: [Robert Boyd, nameHasMultipleBearers, true]
-
A.
hasSurnameBearer
Indicates that a particular surname is borne or carried by a specific person or entity.
-
B.
nameHasVariant
Indicates that an entity’s name has an alternative or variant form.
-
C.
nameBearersUsuallyHaveLegalName
Indicates that entities which bear a certain name typically also possess that name as their official legal name.
-
D.
nameBearerType
Indicates the specific role or capacity in which an entity bears or carries a given name (e.g., as a person, place, organization, or other type of name bearer).
-
E.
typicalNameBearers
Indicates that the subject is a common or characteristic name borne by the entities in the object set.
- F. None of above. chosen
Provenance (4 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_69f224631674819080c8d089674f9f4f |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f67795fdd4819088f3c7d0de598699 |
completed | May 2, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69f66ec8298c8190b41fe9d182c05676 |
completed | May 2, 2026, 9:38 p.m. |
| PDg | Predicate description generation | batch_69f67256d064819094be04fc1bbbc635 |
completed | May 2, 2026, 9:53 p.m. |
Created at: April 29, 2026, 6:15 p.m.