Triple
T32729847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Natolin |
E836917
|
entity |
| Predicate | specializedFieldAtCampus |
P140458
|
FINISHED |
| Object | European Union studies |
—
|
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: European Union studies | Statement: [Natolin, specializedFieldAtCampus, European Union studies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: specializedFieldAtCampus Context triple: [Natolin, specializedFieldAtCampus, European Union studies]
-
A.
isSpecializedCampus
Indicates that a campus is dedicated to a specific field, discipline, or set of specialized programs rather than offering a broad, general curriculum.
-
B.
nearCampusAcademicFocus
Indicates that an entity is located close to a campus and is primarily oriented toward academic or educational activities associated with that campus.
-
C.
campusSector
Indicates that one location or facility is part of, or belongs to, a specific sector or zone within a campus.
-
D.
campusFocus
Indicates that something (such as a program, initiative, or activity) is specifically oriented toward or centered on a particular campus.
-
E.
subjectSpecialization
chosen
Indicates that one subject focuses on, or has expertise in, a particular field, topic, or area of knowledge.
- 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_69f34935fb048190ad4967420581f835 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f7aa699d68819081ed363931894ab3 |
completed | May 3, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69f7a8cec6d48190bebfa884b2f938c0 |
completed | May 3, 2026, 7:58 p.m. |
Created at: May 1, 2026, 1:11 a.m.