Triple
T6645576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berkeley Mansions |
E150690
|
entity |
| Predicate | hasNotableOccupantRole |
P24124
|
FINISHED |
| Object | wealthy bachelor |
—
|
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: wealthy bachelor | Statement: [Berkeley Mansions, hasNotableOccupantRole, wealthy bachelor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableOccupantRole Context triple: [Berkeley Mansions, hasNotableOccupantRole, wealthy bachelor]
-
A.
hasNotableRoleIn
Indicates that an entity holds a significant or noteworthy role or function within another entity, event, work, or context.
-
B.
hasNotableBearerOccupation
Indicates that an entity is associated with a notable person who holds a specific occupation.
-
C.
hasNotableOwner
Indicates that an entity is or has been owned by a person or organization considered notable or significant.
-
D.
hasNotablePosition
Indicates that an entity holds or has held a position, role, or office considered notable or significant.
-
E.
notableHolderRole
chosen
Indicates that an entity is recognized for holding a particular role, office, or position in a notable or distinguished capacity.
- 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_69c687f1a3048190828b7342f7125d5c |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6cc9c6cb0819084fec8e0beb430de |
completed | March 27, 2026, 6:29 p.m. |
| PD | Predicate disambiguation | batch_69c6ad04d66c8190926ffcbff372643b |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2 p.m.