Triple
T30794498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faculty of Humanities, Kharkiv National University of Radioelectronics |
E784189
|
entity |
| Predicate | collaboratesWith |
P37
|
FINISHED |
| Object |
technical faculties of Kharkiv National University of Radioelectronics
The technical faculties of Kharkiv National University of Radioelectronics are the university’s science and engineering divisions focused on training specialists and conducting research in fields such as electronics, computer science, and information technologies.
|
E220357
|
NE 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: technical faculties of Kharkiv National University of Radioelectronics | Statement: [Faculty of Humanities, Kharkiv National University of Radioelectronics, collaboratesWith, technical faculties of Kharkiv National University of Radioelectronics]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: technical faculties of Kharkiv National University of Radioelectronics Triple: [Faculty of Humanities, Kharkiv National University of Radioelectronics, collaboratesWith, technical faculties of Kharkiv National University of Radioelectronics]
Generated description
The technical faculties of Kharkiv National University of Radioelectronics are the university’s science and engineering divisions focused on training specialists and conducting research in fields such as electronics, computer science, and information technologies.
Provenance (5 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_69f224b2e2a48190b19aa43db9da5b67 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f690110f008190a1577560ed7790ed |
completed | May 3, 2026, midnight |
| NED1 | Entity disambiguation (via context triple) | batch_6a28b0ad88e48190b1a484920e132fc8 |
completed | June 10, 2026, 12:32 a.m. |
| NEDg | Description generation | batch_6a28b1ed9b0c8190986159e58593fadf |
completed | June 10, 2026, 12:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a28b2b51afc81908cae8756f6d9b3a1 |
completed | June 10, 2026, 12:41 a.m. |
Created at: April 29, 2026, 8:42 p.m.