Triple

T24236392
Position Surface form Disambiguated ID Type / Status
Subject Θεολογική Σχολή Χάλκης E601897 entity
Predicate locatedNear P294 FINISHED
Object Ισταμπούλ
Η Ισταμπούλ είναι η μεγαλύτερη πόλη της Τουρκίας, ιστορικό και πολιτιστικό κέντρο που εκτείνεται σε Ευρώπη και Ασία και υπήρξε πρωτεύουσα των Βυζαντινής και Οθωμανικής αυτοκρατορίας.
E1626442 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: Ισταμπούλ | Statement: [Θεολογική Σχολή Χάλκης, locatedNear, Ισταμπούλ]
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: Ισταμπούλ
Triple: [Θεολογική Σχολή Χάλκης, locatedNear, Ισταμπούλ]
Generated description
Η Ισταμπούλ είναι η μεγαλύτερη πόλη της Τουρκίας, ιστορικό και πολιτιστικό κέντρο που εκτείνεται σε Ευρώπη και Ασία και υπήρξε πρωτεύουσα των Βυζαντινής και Οθωμανικής αυτοκρατορίας.

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_69e29538aafc8190a2386fdebbd1393b completed April 17, 2026, 8:16 p.m.
NER Named-entity recognition batch_69f28a9b52708190b319a9e502a61d13 completed April 29, 2026, 10:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fbd2dcc348190af8573c4e701cbf1 completed May 22, 2026, 2:19 a.m.
NEDg Description generation batch_6a0fc02c37fc81908bc87756f19be723 completed May 22, 2026, 2:32 a.m.
NED2 Entity disambiguation (via description) batch_6a0fc0da34cc8190a3c7db78058cfcc8 completed May 22, 2026, 2:35 a.m.
Created at: April 18, 2026, 12:02 a.m.