Triple
T8434496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York shirtwaist strike of 1909 |
E199191
|
entity |
| Predicate | hasLanguageOfProtest |
P83346
|
FINISHED |
| Object | Yiddish |
—
|
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: Yiddish | Statement: [New York shirtwaist strike of 1909, hasLanguageOfProtest, Yiddish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageOfProtest Context triple: [New York shirtwaist strike of 1909, hasLanguageOfProtest, Yiddish]
-
A.
hasProtestMovement
Indicates that an entity is associated with, or gives rise to, an organized protest movement opposing or advocating change related to it.
-
B.
protests
Indicates that an entity publicly expresses opposition or disapproval toward another entity, action, or situation.
-
C.
notableProtest
Indicates that an entity is recognized for having led, organized, or been centrally involved in a significant protest or demonstration.
-
D.
languageAdvocated
Indicates that an entity actively supports, promotes, or argues in favor of the use or adoption of a particular language.
-
E.
languageOfPetition
Indicates the language in which a petition is written, submitted, or officially recorded.
- F. None of above. chosen
Provenance (4 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_69ca8314cd6c8190a6b8c2a1096e18f3 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe30fba4081908bfdef3faf5baceb |
completed | March 31, 2026, 3:06 p.m. |
| PD | Predicate disambiguation | batch_69cbd0ec200c8190b0299e2b0b4bdcc2 |
completed | March 31, 2026, 1:49 p.m. |
| PDg | Predicate description generation | batch_69cbe30c2d088190b4cb89adb4e88273 |
completed | March 31, 2026, 3:06 p.m. |
Created at: March 30, 2026, 6:07 p.m.