Triple

T23917006
Position Surface form Disambiguated ID Type / Status
Subject Old Yishuv of Jerusalem E602109 entity
Predicate developedNeighborhood P111159 FINISHED
Object Mea Shearim
Mea Shearim is one of Jerusalem’s oldest ultra-Orthodox Jewish neighborhoods, known for its strict religious observance, traditional lifestyle, and distinctive 19th-century character.
E1622969 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: Mea Shearim | Statement: [Old Yishuv of Jerusalem, developedNeighborhood, Mea Shearim]
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: Mea Shearim
Triple: [Old Yishuv of Jerusalem, developedNeighborhood, Mea Shearim]
Generated description
Mea Shearim is one of Jerusalem’s oldest ultra-Orthodox Jewish neighborhoods, known for its strict religious observance, traditional lifestyle, and distinctive 19th-century character.

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_69e2953a187081908346a9f36e85fc98 completed April 17, 2026, 8:16 p.m.
NER Named-entity recognition batch_69f1ce9a744c819080bd30176b8de9a0 completed April 29, 2026, 9:25 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0facf6248c8190b63a12d01609339d completed May 22, 2026, 1:10 a.m.
NEDg Description generation batch_6a0fad96501481909a63e86e7e0d6ca7 completed May 22, 2026, 1:12 a.m.
NED2 Entity disambiguation (via description) batch_6a0fae34bb948190b8f936d8f47d7c41 completed May 22, 2026, 1:15 a.m.
Created at: April 17, 2026, 8:40 p.m.