Triple
T7614741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 5th Special Forces Group (Airborne) |
E172332
|
entity |
| Predicate | languageDesignation |
P50222
|
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: [5th Special Forces Group (Airborne), languageDesignation, Arabic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageDesignation Context triple: [5th Special Forces Group (Airborne), languageDesignation, Arabic]
-
A.
languageName
Indicates the specific name assigned to a language in the relationship.
-
B.
languageDesigned
Indicates that one entity created or developed the language used or associated with another entity.
-
C.
languageLabel
chosen
Indicates the human-readable name or label of a language associated with an entity or resource.
-
D.
languageOfWorkOrName
Indicates the language in which a work is created or a name is expressed.
-
E.
languageSpecifies
Indicates that one entity defines or constrains the syntax, semantics, or usage rules that govern how another language or linguistic system is expressed or interpreted.
- 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_69c6994f50808190ba228764bb422417 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6fa4392e881908ed1ab3f64b41600 |
completed | March 27, 2026, 9:44 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e485f88190910b39da52a955fe |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:55 p.m.