Triple
T26688377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Makhlouf family |
E672810
|
entity |
| Predicate | roleDuringSyrianCivilWar |
P108011
|
FINISHED |
| Object | key financial backer of Syrian government |
—
|
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: key financial backer of Syrian government | Statement: [Makhlouf family, roleDuringSyrianCivilWar, key financial backer of Syrian government]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleDuringSyrianCivilWar Context triple: [Makhlouf family, roleDuringSyrianCivilWar, key financial backer of Syrian government]
-
A.
roleInLibyanCivilWar
Indicates the specific involvement, function, or position an entity had in the context of the Libyan Civil War.
-
B.
politicalStatusInSyria
Indicates the political role, position, or standing that an entity holds within the context of Syria.
-
C.
roleInWarOrConflict
chosen
Indicates the specific function, position, or involvement an entity has within a particular war or conflict.
-
D.
roleInIraq
Indicates that an entity holds or held a specific role, position, or function in the context of Iraq.
-
E.
legalStatusInSyria
Indicates the legal status or condition an entity holds under the laws and regulations of Syria.
- 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_69eecda2066c8190a344218afa5e89c1 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f61740943481909344a18e94de5b20 |
completed | May 2, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69f60b8bb0d08190ab5a9a2a8847c6f4 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 27, 2026, 3:24 a.m.