Triple
T14073206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hawza |
E338663
|
entity |
| Predicate | entryLevel |
P25096
|
FINISHED |
| Object | introductory studies (muqaddimat) |
—
|
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: introductory studies (muqaddimat) | Statement: [Hawza, entryLevel, introductory studies (muqaddimat)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: entryLevel Context triple: [Hawza, entryLevel, introductory studies (muqaddimat)]
-
A.
entryLevelCredential
Indicates that a credential qualifies someone for initial or beginner-level entry into a field, role, or program.
-
B.
trainingLevel
Indicates the degree or stage of training or skill development that an entity has attained.
-
C.
levelServed
Indicates that a particular service, function, or resource is provided or made available at a specified level or tier.
-
D.
levels
Indicates that one entity adjusts, equalizes, or smooths out the height, intensity, or degree of another entity.
-
E.
admissionsLevel
chosen
Indicates the degree or category of access, entry, or acceptance granted in an admissions 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_69d81c687b0c819087fd9ed4198403f8 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5c5bc49881909012b66fa451f495 |
completed | April 14, 2026, 3:25 p.m. |
| PD | Predicate disambiguation | batch_69de05b0e6c88190a819eeba0028981f |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:21 p.m.