Triple

T25993379
Position Surface form Disambiguated ID Type / Status
Subject Beyazıt Square E646419 entity
Predicate hasAlternativeName P39 FINISHED
Object Forum of Theodosius
The Forum of Theodosius was a major public square and monumental forum of late Roman Constantinople, known for its grand column and role as a political and ceremonial center of the city.
E1703364 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: Forum of Theodosius | Statement: [Beyazıt Square, hasAlternativeName, Forum of Theodosius]
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: Forum of Theodosius
Triple: [Beyazıt Square, hasAlternativeName, Forum of Theodosius]
Generated description
The Forum of Theodosius was a major public square and monumental forum of late Roman Constantinople, known for its grand column and role as a political and ceremonial center of the city.

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_69e77e88cb8481908da31d4a00661f55 completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f60549019c81909fb687c81d9ac27d completed May 2, 2026, 2:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1107988b448190917ee96295b0373d completed May 23, 2026, 1:49 a.m.
NEDg Description generation batch_6a11085043a08190b86f770075f609c1 completed May 23, 2026, 1:52 a.m.
NED2 Entity disambiguation (via description) batch_6a110925bec881908c0bdb63355e4e31 completed May 23, 2026, 1:55 a.m.
Created at: April 22, 2026, 8:57 a.m.