Triple

T24000801
Position Surface form Disambiguated ID Type / Status
Subject Büyük Postane E594243 entity
Predicate alsoKnownAs P39 FINISHED
Object Büyük Postane Binası
Büyük Postane Binası is a historic late 19th-century Ottoman post office building in Istanbul, renowned for its grand architecture and role as a central postal hub.
E1613015 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: Büyük Postane Binası | Statement: [Büyük Postane, alsoKnownAs, Büyük Postane Binası]
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: Büyük Postane Binası
Triple: [Büyük Postane, alsoKnownAs, Büyük Postane Binası]
Generated description
Büyük Postane Binası is a historic late 19th-century Ottoman post office building in Istanbul, renowned for its grand architecture and role as a central postal hub.

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_69e288b9ecf08190b8c94a278f5674fe completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1d464f1988190a0a9352c1ec214eb completed April 29, 2026, 9:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f7e969554819087c6237d2e5f75cf completed May 21, 2026, 9:52 p.m.
NEDg Description generation batch_6a0f7f4da3048190af7ef06dcec0a651 completed May 21, 2026, 9:55 p.m.
NED2 Entity disambiguation (via description) batch_6a0f800c3e4c8190ae281aba47e36941 completed May 21, 2026, 9:58 p.m.
Created at: April 17, 2026, 9:39 p.m.