Triple

T37682182
Position Surface form Disambiguated ID Type / Status
Subject thermal baths of Çekirge E938263 entity
Predicate locatedIn P40 FINISHED
Object Çekirge neighborhood
Çekirge neighborhood is a historic district in Bursa, Turkey, renowned for its natural hot springs, spa culture, and traditional thermal bath complexes.
E2238282 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: Çekirge neighborhood | Statement: [thermal baths of Çekirge, locatedIn, Çekirge neighborhood]
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: Çekirge neighborhood
Triple: [thermal baths of Çekirge, locatedIn, Çekirge neighborhood]
Generated description
Çekirge neighborhood is a historic district in Bursa, Turkey, renowned for its natural hot springs, spa culture, and traditional thermal bath complexes.

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_69f76ed881408190bc62a969530a4a53 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fbadf966f88190b4a3be1500b0f958 completed May 6, 2026, 9:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40ba6883288190ae4e71d32e955c5e completed June 28, 2026, 6:08 a.m.
NEDg Description generation batch_6a40bafeb4f881908d346e5b04b5fe6d completed June 28, 2026, 6:11 a.m.
NED2 Entity disambiguation (via description) batch_6a40bd1836b08190a0754bb4e3d8caeb completed June 28, 2026, 6:20 a.m.
Created at: May 3, 2026, 4:18 p.m.