Triple
T38323465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | First Quarter Storm protests |
E1036718
|
entity |
| Predicate | languageOfProtests |
P83346
|
FINISHED |
| Object | Filipino |
E1182
|
NE 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: Filipino | Statement: [First Quarter Storm protests, languageOfProtests, Filipino]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfProtests Context triple: [First Quarter Storm protests, languageOfProtests, Filipino]
-
A.
hasLanguageOfProtest
chosen
Indicates that an entity expresses or embodies a language, style, or discourse of protest in relation to another entity or context.
-
B.
languageOfPropaganda
Indicates that a particular language is used as the medium or vehicle for disseminating propaganda.
-
C.
languageOfPoliticalContext
Indicates the language in which a given political context, discourse, or situation is expressed or conducted.
-
D.
languageOfCampaigning
Indicates the language used to conduct or communicate a campaign (e.g., political, marketing, or advocacy efforts).
-
E.
languageOfPetition
Indicates the language in which a petition is written, submitted, or officially recorded.
- F. None of above.
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_69f76e1c16fc8190bde982289dd5106b |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a020ec13d808190b41acdc31adc4191 |
completed | May 11, 2026, 5:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a41a7e16aac8190815325f6d200f8c9 |
completed | June 28, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_6a020d9259c08190ad0370091c23ea8a |
completed | May 11, 2026, 5:10 p.m. |
Created at: May 3, 2026, 4:30 p.m.