Triple

T35642502
Position Surface form Disambiguated ID Type / Status
Subject Kızılay Square E1029909 entity
Predicate locatedOnStreet P959 FINISHED
Object İnkilap Street
İnkilap Street is a central thoroughfare in Ankara, Turkey, known for hosting the prominent Kızılay Square and serving as a key hub of urban activity.
 E2155669 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: İnkilap Street | Statement: [Kızılay Square, locatedOnStreet, İnkilap Street]
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: İnkilap Street
Triple: [Kızılay Square, locatedOnStreet, İnkilap Street]
Generated description
İnkilap Street is a central thoroughfare in Ankara, Turkey, known for hosting the prominent Kızılay Square and serving as a key hub of urban activity.

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_69f76e087bdc8190a4794bf9c0bd7634 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79f4c6cc881909f1d101afa35b555 completed May 3, 2026, 7:17 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38914f56c88190828a8f3bbd78a053 completed June 22, 2026, 1:35 a.m.
NEDg Description generation batch_6a3891dc79dc8190bf2482158e0dabed completed June 22, 2026, 1:37 a.m.
NED2 Entity disambiguation (via description) batch_6a38925d7c688190afca1a703aea06c3 completed June 22, 2026, 1:39 a.m.
Created at: May 3, 2026, 4:05 p.m.