Triple
T32812968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ιωάννα Μούσχουρη |
E839203
|
entity |
| Predicate | educatedAt |
P5
|
FINISHED |
| Object |
Εθνικό Ωδείο Αθηνών
Το Εθνικό Ωδείο Αθηνών είναι ένα από τα παλαιότερα και σημαντικότερα μουσικά εκπαιδευτικά ιδρύματα της Ελλάδας, με καθοριστική συμβολή στη διαμόρφωση της ελληνικής μουσικής παιδείας.
|
E2023198
|
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: Εθνικό Ωδείο Αθηνών | Statement: [Ιωάννα Μούσχουρη, educatedAt, Εθνικό Ωδείο Αθηνών]
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: Εθνικό Ωδείο Αθηνών Triple: [Ιωάννα Μούσχουρη, educatedAt, Εθνικό Ωδείο Αθηνών]
Generated description
Το Εθνικό Ωδείο Αθηνών είναι ένα από τα παλαιότερα και σημαντικότερα μουσικά εκπαιδευτικά ιδρύματα της Ελλάδας, με καθοριστική συμβολή στη διαμόρφωση της ελληνικής μουσικής παιδείας.
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_69f3493d35208190b4351b4e85f2fa16 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6cdcb87dc819096424c386f7a44bf |
completed | May 3, 2026, 4:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a34b17c44c48190bd6785d9bcf68e8c |
completed | June 19, 2026, 3:03 a.m. |
| NEDg | Description generation | batch_6a34b29d06088190a46ae528f21056e9 |
completed | June 19, 2026, 3:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a34b31c85108190a684cf1750b560f5 |
completed | June 19, 2026, 3:10 a.m. |
Created at: May 1, 2026, 1:15 a.m.