Triple
T25656104
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bengali Language Movement |
E643239
|
entity |
| Predicate | opposedLanguage |
P437
|
FINISHED |
| Object | Urdu-only policy |
—
|
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: Urdu-only policy | Statement: [Bengali Language Movement, opposedLanguage, Urdu-only policy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: opposedLanguage Context triple: [Bengali Language Movement, opposedLanguage, Urdu-only policy]
-
A.
opposedBy
chosen
Indicates that one entity actively resists, disagrees with, or works against the actions, views, or position of another entity.
-
B.
opposite
Indicates that one entity is positioned or oriented directly across from, or in a contrary or reverse relation to, another entity.
-
C.
opposesPhrase
Indicates that one entity expresses disagreement with, resistance to, or argument against the idea, statement, or position represented by the phrase.
-
D.
opposedTextType
Indicates that one text type stands in opposition or contrast to another text type.
-
E.
opposesLabel
Indicates that one entity expresses disagreement with, resistance to, or active opposition against another entity or its position.
- 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_69e77e7d8a848190a98d0162325fd780 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f650c70d7c819093d9a0f005f7c8d5 |
completed | May 2, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69f64cab1f648190a2a9460690d18a37 |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 21, 2026, 6:33 p.m.