Triple
T16390793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Galatasaray University |
E398044
|
entity |
| Predicate | hasSpecialQuota |
P123232
|
FINISHED |
| Object | graduates of Galatasaray High School |
—
|
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: graduates of Galatasaray High School | Statement: [Galatasaray University, hasSpecialQuota, graduates of Galatasaray High School]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpecialQuota Context triple: [Galatasaray University, hasSpecialQuota, graduates of Galatasaray High School]
-
A.
hasSpecial
Indicates that an entity possesses or is associated with a distinctive or exceptional attribute, status, or feature compared to others.
-
B.
hasSpecialRules
Indicates that certain entities are governed by additional or exceptional rules that differ from the standard ones.
-
C.
hasSpecialMerit
Indicates that an entity possesses exceptional or noteworthy qualities that distinguish it from others in a positive way.
-
D.
hasNumberOfSpecials
Indicates that an entity is associated with a specific count of special items, features, or occurrences.
-
E.
hasSpecialCategory
Indicates that an entity is associated with a designated special or exceptional category distinct from its standard classifications.
- 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_69d87f2880b48190ae1a9673a3bbef80 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e326425c8081908cacffcfa8c7386b |
completed | April 18, 2026, 6:35 a.m. |
| PD | Predicate disambiguation | batch_69e226f94dd48190b7b8e0e983738a67 |
completed | April 17, 2026, 12:26 p.m. |
| PDg | Predicate description generation | batch_69e24555bb6c8190977cf5c5f9149056 |
completed | April 17, 2026, 2:36 p.m. |
Created at: April 10, 2026, 5:08 a.m.