Triple
T13831486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moroccan |
E332408
|
entity |
| Predicate | spelledInArabic |
P6450
|
FINISHED |
| Object | مغربي |
—
|
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: مغربي | Statement: [Moroccan, spelledInArabic, مغربي]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spelledInArabic Context triple: [Moroccan, spelledInArabic, مغربي]
-
A.
verseTextArabic
Indicates the Arabic-language text content associated with a specific verse in a scriptural or poetic work.
-
B.
lengthInArabicWordsApprox
Indicates that the approximate length of something is expressed in Arabic words.
-
C.
revealedInArabicOrder
Indicates that something was disclosed or made known following the original sequence in which it was revealed in Arabic.
-
D.
hasNameInArabic
chosen
Indicates that an entity is associated with a specific name expressed in the Arabic language.
-
E.
spellsOut
Indicates that one entity explicitly writes, states, or presents another entity in full detail, often by expanding an abbreviation, code, or symbolic form into its complete representation.
- 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_69d81c5ae7c88190b0dd41bdafeb5999 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0299334481908c2b271eaf06e4b7 |
completed | April 14, 2026, 9:02 a.m. |
| PD | Predicate disambiguation | batch_69dbc86668e08190ba9135d1c3f38d35 |
completed | April 12, 2026, 4:29 p.m. |
Created at: April 9, 2026, 10:13 p.m.