Triple
T16612055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Babs |
E403598
|
entity |
| Predicate | hasFictionalManager |
P86010
|
FINISHED |
| Object | Las Vegas showgirls' manager in Blansky's Beauties |
—
|
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: Las Vegas showgirls' manager in Blansky's Beauties | Statement: [Babs, hasFictionalManager, Las Vegas showgirls' manager in Blansky's Beauties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalManager Context triple: [Babs, hasFictionalManager, Las Vegas showgirls' manager in Blansky's Beauties]
-
A.
hasFictionalStaffMember
Indicates that an entity includes or employs a staff member who is a fictional character.
-
B.
hasFictionalNetworkExecutive
Indicates that an entity is associated with a fictional character who serves as a network executive.
-
C.
managedByFictionalCharacter
Indicates that an entity is overseen, directed, or run under the authority or control of a fictional character.
-
D.
fictionalManager
chosen
Indicates that one entity serves as the (possibly invented or non-real) manager of another entity.
-
E.
hasFictionalLeader
Indicates that an entity is led or governed by a leader who is a fictional character rather than a real person.
- 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_69d883880d0c81908b5fcd454e767b60 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e36096356c819092815d64db041793 |
completed | April 18, 2026, 10:44 a.m. |
| PD | Predicate disambiguation | batch_69e296aabc508190b3836a91b49113ad |
completed | April 17, 2026, 8:23 p.m. |
Created at: April 10, 2026, 5:17 a.m.