Triple
T32838613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | بحر المتقارب |
E839901
|
entity |
| Predicate | يُعد مناسباً لـ |
P18991
|
FINISHED |
| Object | التعبير عن الانفعال القوي |
—
|
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: التعبير عن الانفعال القوي | Statement: [بحر المتقارب, يُعد مناسباً لـ, التعبير عن الانفعال القوي]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: يُعد مناسباً لـ Context triple: [بحر المتقارب, يُعد مناسباً لـ, التعبير عن الانفعال القوي]
-
A.
isSuitableFor
chosen
Indicates that one entity is appropriate, fitting, or well-matched for use, application, or association with another entity.
-
B.
lessSuitableFor
Indicates that one entity is comparatively less appropriate, effective, or fitting than another for a given purpose, context, or condition.
-
C.
isPerfectFor
Indicates that one entity is ideally suited or optimally appropriate for another entity, purpose, or context.
-
D.
adjustsFor
Indicates that one entity modifies, compensates, or accounts for the effects of another entity to achieve a corrected or normalized result.
-
E.
effectiveFor
Indicates that one entity successfully produces the intended effect, benefit, or desired outcome for another entity or condition.
- 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_69f3493ff0888190b51e974eae2a7834 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6ce6d659881909ddcec1d2966e020 |
completed | May 3, 2026, 4:26 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1667a48190b42684f6ec22dae9 |
completed | May 3, 2026, 4:16 a.m. |
Created at: May 1, 2026, 1:16 a.m.