Triple
T11404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carnegie Steel Company |
E232
|
entity |
| Predicate | employed |
P7
|
FINISHED |
| Object | tens of thousands of workers |
—
|
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: tens of thousands of workers | Statement: [Carnegie Steel Company, employed, tens of thousands of workers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: employed Context triple: [Carnegie Steel Company, employed, tens of thousands of workers]
-
A.
employer
chosen
Indicates a relationship where one entity hires, pays, and oversees the work of another entity.
-
B.
worksWith
Indicates that two entities collaborate or perform tasks together in a shared work-related context.
-
C.
fieldOfWork
Indicates the professional or academic domain in which an entity is primarily engaged or specializes.
-
D.
role
Indicates the function, position, or responsibility that one entity holds in relation to another within a given context.
-
E.
commissionedBy
Indicates that one entity has been formally requested, authorized, or hired by another entity to create, perform, or carry out something.
- 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_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a241ea1ea081908e8a81ca97531ba5 |
completed | Feb. 28, 2026, 1:16 a.m. |
| PD | Predicate disambiguation | batch_69a23fe7da8c8190aea795b62cb91621 |
completed | Feb. 28, 2026, 1:07 a.m. |
Created at: Feb. 28, 2026, 1:02 a.m.