Triple
T1285700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lebanese American University |
E27428
|
entity |
| Predicate | followsSystem |
P26745
|
FINISHED |
| Object | American-style education system |
—
|
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: American-style education system | Statement: [Lebanese American University, followsSystem, American-style education system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: followsSystem Context triple: [Lebanese American University, followsSystem, American-style education system]
-
A.
follows
Indicates that one entity comes after, moves behind, or acts in accordance with another entity in time, space, or sequence.
-
B.
followsWork
Indicates that one work (such as a publication, version, or creative piece) comes directly after another in sequence or succession.
-
C.
followsStage
Indicates that one stage occurs after and in sequence with another stage in a process or workflow.
-
D.
followerOf
Indicates that one entity subscribes to, tracks, or regularly receives updates from another entity, typically in a social or informational context.
-
E.
followsFrom
Indicates that one fact, event, or state logically or causally results from, is implied by, or comes as a consequence of another.
- F. None of above. chosen
Provenance (4 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_69a496d4ec448190ad653b2590c46711 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c0b85eb48190a8b61dc397fa6390 |
completed | March 1, 2026, 10:42 p.m. |
| PD | Predicate disambiguation | batch_69a4bee276d8819092f71c5a1140bb61 |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4bf60545c8190901ccfb2cb7c4b41 |
completed | March 1, 2026, 10:36 p.m. |
Created at: March 1, 2026, 7:51 p.m.