Triple
T27172595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | عماد فايز مغنية |
E682959
|
entity |
| Predicate | الاسم باللغة الإنجليزية |
P3437
|
FINISHED |
| Object | Imad Fayez Mughniyeh |
—
|
NE NERFINISHED |
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: Imad Fayez Mughniyeh | Statement: [عماد فايز مغنية, الاسم باللغة الإنجليزية, Imad Fayez Mughniyeh]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: الاسم باللغة الإنجليزية Context triple: [عماد فايز مغنية, الاسم باللغة الإنجليزية, Imad Fayez Mughniyeh]
-
A.
hasEnglishName
chosen
Indicates that an entity is associated with a name expressed in the English language.
-
B.
hasOfficialNameInEnglish
Indicates that an entity has an officially recognized name expressed in the English language.
-
C.
nameInOriginalLanguage
Indicates that an entity’s name is given in its original or native language form.
-
D.
hasEnglishNameMeaning
Indicates that an entity is associated with an English-language name along with the meaning or semantic interpretation of that name.
-
E.
hasLaterNameInEnglish
Indicates that an entity is known by a different English name at a later time or in a subsequent context.
- 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_69eefad086808190ab89816c0c300476 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f62549039c8190af7159d07416c985 |
completed | May 2, 2026, 4:24 p.m. |
| PD | Predicate disambiguation | batch_69f623a91b9c8190b2e2fdbc55cb89b6 |
completed | May 2, 2026, 4:17 p.m. |
Created at: April 27, 2026, 9:24 a.m.