Triple
T18497072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 25 January Revolution (opening day) |
E451974
|
entity |
| Predicate | hasLanguageOfProtestSigns |
P83346
|
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: [25 January Revolution (opening day), hasLanguageOfProtestSigns, Arabic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageOfProtestSigns Context triple: [25 January Revolution (opening day), hasLanguageOfProtestSigns, Arabic]
-
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.
hasProtestMovement
Indicates that an entity is associated with, or gives rise to, an organized protest movement opposing or advocating change related to it.
-
C.
hasSignificantLanguage
Indicates that an entity possesses a language that plays an important or primary role in its communication, identity, or functioning.
-
D.
languageOfSignatures
Indicates the language in which the signatures on a document or agreement are written or expressed.
-
E.
protests
Indicates that an entity publicly expresses opposition or disapproval toward another entity, action, or situation.
- 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_69e532c15dec8190941e7c7a4cdebb66 |
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, 11:36 a.m.