Triple
T37331391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kirby and Co. |
E926759
|
entity |
| Predicate | employerOfProtagonistGroupMember |
P93486
|
FINISHED |
| Object | Alice Sycamore |
—
|
NE NERFINISHED |
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: Alice Sycamore | Statement: [Kirby and Co., employerOfProtagonistGroupMember, Alice Sycamore]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: employerOfProtagonistGroupMember Context triple: [Kirby and Co., employerOfProtagonistGroupMember, Alice Sycamore]
-
A.
employerInPlot
chosen
Indicates that one entity serves as the employer of another within the context of a specific plot or storyline.
-
B.
employerIn
Indicates that one entity serves as the employer of another within a specified context, such as a location, organization, or time period.
-
C.
employerOrStudio
Indicates that one entity serves as the employing organization or production studio responsible for the work or activities of another entity.
-
D.
employerOrPartner
Indicates that one entity is either the employer of, or a business partner with, another entity.
-
E.
parentEmployer
Indicates that one organization is the direct or higher-level employer of another organization or entity.
- 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_69f76eb386d88190a8d511aa11540dfc |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcf825ca7081909d06b0df33eb33f9 |
completed | May 7, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69fcf42160f0819096812a8bf590875e |
completed | May 7, 2026, 8:20 p.m. |
Created at: May 3, 2026, 4:16 p.m.