Triple
T22527019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | نهر الحب |
E556932
|
entity |
| Predicate | حوار |
P114797
|
FINISHED |
| Object | حوار باللغة العربية الفصحى والعامية المصرية |
—
|
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: حوار باللغة العربية الفصحى والعامية المصرية | Statement: [نهر الحب, حوار, حوار باللغة العربية الفصحى والعامية المصرية]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: حوار Context triple: [نهر الحب, حوار, حوار باللغة العربية الفصحى والعامية المصرية]
-
A.
dialogue
chosen
Indicates that two or more entities are engaged in an exchange of spoken or written communication with each other.
-
B.
dialogueType
Indicates the specific kind or category of dialogue occurring between entities (e.g., question-answer, negotiation, instruction).
-
C.
dialoguesBy
Indicates that one entity is the creator, author, or source of the dialogues associated with another entity.
-
D.
dialogueWith
Indicates that two entities are engaged in a mutual conversational exchange or dialogue with each other.
-
E.
dialogueFeature
Indicates that one entity exhibits or involves a particular characteristic, property, or element of a dialogue or conversational exchange with another entity.
- 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_69e11e57483c8190b0887c4f8ff26446 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15ed411488190a51320930b9805c2 |
completed | April 29, 2026, 1:28 a.m. |
| PD | Predicate disambiguation | batch_69e898c864148190a3f5feec7967d49c |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:51 p.m.