Triple
T18496359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | February 1 2011 million-man march |
E451957
|
entity |
| Predicate | languageOfProtestSigns |
P4196
|
FINISHED |
| Object | Arabic |
—
|
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: Arabic | Statement: [February 1 2011 million-man march, languageOfProtestSigns, Arabic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfProtestSigns Context triple: [February 1 2011 million-man march, languageOfProtestSigns, Arabic]
-
A.
hasLanguageOfProtest
Indicates that an entity expresses or embodies a language, style, or discourse of protest in relation to another entity or context.
-
B.
languageOfSignatures
Indicates the language in which the signatures on a document or agreement are written or expressed.
-
C.
officialLanguageOfSignage
Indicates that a particular language is the one officially used on public signs and signage within a given place or context.
-
D.
languageOfPropaganda
Indicates that a particular language is used as the medium or vehicle for disseminating propaganda.
-
E.
languageOfSignage
chosen
Indicates the language used on signs or written displays associated with an entity.
- 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_69d8d3855d50819097fc8561b0299dd9 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e532c09a8081909cf0b44df3682bb8 |
completed | April 19, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69e469dbf5208190b6fc49e02a087f54 |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:35 a.m.