Triple
T21445802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1968 Ford sewing machinists strike |
E529071
|
entity |
| Predicate | affectedProcess |
P112258
|
FINISHED |
| Object | car seat cover production |
—
|
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: car seat cover production | Statement: [1968 Ford sewing machinists strike, affectedProcess, car seat cover production]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: affectedProcess Context triple: [1968 Ford sewing machinists strike, affectedProcess, car seat cover production]
-
A.
affectsProcess
chosen
Indicates that one entity has an influence on, alters, or changes the course or outcome of a process.
-
B.
affectedProvision
Indicates that a particular legal provision is impacted, modified, or influenced by another action, decision, or provision.
-
C.
affectedProject
Indicates that one entity has an impact on, or is influenced by, a particular project.
-
D.
affectedFunction
Indicates that one entity has an impact on, alters, or impairs the operation or behavior of another entity’s function.
-
E.
affectedEntity
Indicates that an entity is the one that is impacted, influenced, or acted upon as a result of an event, action, or process.
- 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_69e0c457579481909db68053ed99750c |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e8b707ecd88190b3576b8923840870 |
completed | April 22, 2026, 11:54 a.m. |
| PD | Predicate disambiguation | batch_69e631df1b38819088d3604854e697b4 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:05 p.m.