Triple
T21445951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ford sewing machinists |
E529074
|
entity |
| Predicate | laterResult |
P13710
|
FINISHED |
| Object | eventual move to 100 percent of male rate |
—
|
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: eventual move to 100 percent of male rate | Statement: [Ford sewing machinists, laterResult, eventual move to 100 percent of male rate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterResult Context triple: [Ford sewing machinists, laterResult, eventual move to 100 percent of male rate]
-
A.
laterStatus
chosen
Indicates that one entity represents a subsequent or resulting status or condition of another entity in time.
-
B.
laterFlag
Indicates that one event, state, or action occurs at a time later than another referenced event, state, or action.
-
C.
laterDuration
Indicates that one event or time interval occurs after another and lasts for a specified duration.
-
D.
laterTask
Indicates that one task occurs after another in time, representing a temporal ordering where the first task precedes the laterTask.
-
E.
laterIn
Indicates that one event, state, or time point occurs after another in temporal order.
- 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.