Triple
T35351954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James O. McKinsey |
E1020903
|
entity |
| Predicate | hasEmployerClient |
P82055
|
FINISHED |
| Object | Marshall Field & Company |
—
|
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: Marshall Field & Company | Statement: [James O. McKinsey, hasEmployerClient, Marshall Field & Company]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEmployerClient Context triple: [James O. McKinsey, hasEmployerClient, Marshall Field & Company]
-
A.
employerOrPrimaryClient
Indicates that one entity serves as the main employer or principal client of another entity in a work or service relationship.
-
B.
hasEmployees
Indicates that one entity employs one or more other entities as its workers or staff.
-
C.
hasIndustrialEmployer
Indicates that an entity is employed by, or has an employment relationship with, an industrial organization or company.
-
D.
employsOrEmployed
Indicates that one entity currently employs or previously employed another entity in a work or service relationship.
-
E.
hasNotableClientWork
chosen
Indicates that an entity has performed significant or noteworthy work or services for a particular client.
- 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_69f76decd95c8190ae428f6a19d535de |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f79f48acec8190a9d5964581a94f6c |
completed | May 3, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69f79e4888248190be2f63cdfb5cd7b7 |
completed | May 3, 2026, 7:13 p.m. |
Created at: May 3, 2026, 4:03 p.m.