Triple

T30339852
Position Surface form Disambiguated ID Type / Status
Subject A Girl in Black E771716 entity
Predicate hasTitleInGreek P31436 FINISHED
Object Το Κορίτσι με τα Μαύρα
Το Κορίτσι με τα Μαύρα είναι ελληνική δραματική ταινία του 1956 σε σκηνοθεσία Μιχάλη Κακογιάννη, που αφηγείται την ιστορία μιας νεαρής χήρας σε ένα νησί της μεταπολεμικής Ελλάδας.
E1909275 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: Το Κορίτσι με τα Μαύρα | Statement: [A Girl in Black, hasTitleInGreek, Το Κορίτσι με τα Μαύρα]
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: Το Κορίτσι με τα Μαύρα
Triple: [A Girl in Black, hasTitleInGreek, Το Κορίτσι με τα Μαύρα]
Generated description
Το Κορίτσι με τα Μαύρα είναι ελληνική δραματική ταινία του 1956 σε σκηνοθεσία Μιχάλη Κακογιάννη, που αφηγείται την ιστορία μιας νεαρής χήρας σε ένα νησί της μεταπολεμικής Ελλάδας.

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_69f2248b9a208190bc3e6804acd5afd6 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68201f39c8190b53fc2db7b98dcfb completed May 2, 2026, 11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a277c23a8108190aee266da48a76b0a completed June 9, 2026, 2:36 a.m.
NEDg Description generation batch_6a277cc044648190aac2bc5da147e485 completed June 9, 2026, 2:38 a.m.
NED2 Entity disambiguation (via description) batch_6a277d44cc208190aa60636c8df63242 completed June 9, 2026, 2:41 a.m.
Created at: April 29, 2026, 7:55 p.m.