Triple
T66739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arabic |
E1330
|
entity |
| Predicate | hasMorphologicalFeature |
P1250
|
FINISHED |
| Object | root-and-pattern morphology |
—
|
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: root-and-pattern morphology | Statement: [Arabic, hasMorphologicalFeature, root-and-pattern morphology]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMorphologicalFeature Context triple: [Arabic, hasMorphologicalFeature, root-and-pattern morphology]
-
A.
hasMorphologicalType
chosen
Indicates that an entity possesses or is classified by a particular morphological type or structural form.
-
B.
hasGrammaticalGender
Indicates that one entity assigns or possesses a specific grammatical gender in relation to another entity (such as a word, phrase, or linguistic unit).
-
C.
hasVariantSpelling
Indicates that one term is an alternative spelling form of another term.
-
D.
hasFullForm
Indicates that one entity is the complete, expanded, or unabbreviated form of another entity.
-
E.
hasCognate
Indicates that two linguistic forms in different languages share a common historical origin, typically descending from the same ancestral word.
- 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_69a24ba4f760819081f6638a3c70538a |
completed | Feb. 28, 2026, 1:57 a.m. |
| NER | Named-entity recognition | batch_69a2509b5a088190bb9d2b650aeb8bca |
completed | Feb. 28, 2026, 2:19 a.m. |
| PD | Predicate disambiguation | batch_69a24ea749788190bc17865171ff909a |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:02 a.m.