Triple

T33755222
Position Surface form Disambiguated ID Type / Status
Subject Shuafat Refugee Camp E864958 entity
Predicate replaced P101 FINISHED
Object Musrara refugee camp
Musrara refugee camp was an early Palestinian refugee settlement in Jerusalem that was later dismantled and its residents relocated to the Shuafat Refugee Camp.
E2073040 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: Musrara refugee camp | Statement: [Shuafat Refugee Camp, replaced, Musrara refugee camp]
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: Musrara refugee camp
Triple: [Shuafat Refugee Camp, replaced, Musrara refugee camp]
Generated description
Musrara refugee camp was an early Palestinian refugee settlement in Jerusalem that was later dismantled and its residents relocated to the Shuafat Refugee Camp.

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_69f3498c35f881909df279ae4270f831 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6fc5bb4c8819097ca41bcc7fa5e71 completed May 3, 2026, 7:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a368226fe8c819099a2b332baab128a completed June 20, 2026, 12:05 p.m.
NEDg Description generation batch_6a36831f01fc8190a5e2026f6039883d completed June 20, 2026, 12:10 p.m.
NED2 Entity disambiguation (via description) batch_6a36845c22bc819083a9cbe9c3f3be9a completed June 20, 2026, 12:15 p.m.
Created at: May 1, 2026, 1:45 a.m.