Triple
T37352688
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kleinfeld Bridal |
E927366
|
entity |
| Predicate | hasNotableStaffRole |
P108233
|
FINISHED |
| Object | bridal consultant |
—
|
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: bridal consultant | Statement: [Kleinfeld Bridal, hasNotableStaffRole, bridal consultant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableStaffRole Context triple: [Kleinfeld Bridal, hasNotableStaffRole, bridal consultant]
-
A.
hasNotableRoleIn
Indicates that an entity holds a significant or noteworthy role or function within another entity, event, work, or context.
-
B.
hadStaffRole
chosen
Indicates that an entity served in a specific staff role or position for another entity during some period.
-
C.
hasAdultStaffRole
Indicates that an entity holds a staff position or role designated specifically for adults.
-
D.
hasNotableCrewMember
Indicates that an entity is associated with a crew member who is considered notable or distinguished in some way.
-
E.
hasNotableGuestRole
Indicates that an entity appears in a significant but non-starring guest role in relation to another entity, such as a show, episode, or production.
- 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_69f76eb5e034819088e53ab5b7909a68 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a13a1308190a202df66f4781855 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:16 p.m.