Triple

T33718255
Position Surface form Disambiguated ID Type / Status
Subject Kufr Aqab E863935 entity
Predicate alternativeTransliteration P5923 FINISHED
Object Kafr ‘Aqab
Kafr ‘Aqab is a Palestinian neighborhood on the northeastern outskirts of Jerusalem, located beyond the Israeli separation barrier and characterized by dense urban development and complex administrative status.
E2064511 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: Kafr ‘Aqab | Statement: [Kufr Aqab, alternativeTransliteration, Kafr ‘Aqab]
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: Kafr ‘Aqab
Triple: [Kufr Aqab, alternativeTransliteration, Kafr ‘Aqab]
Generated description
Kafr ‘Aqab is a Palestinian neighborhood on the northeastern outskirts of Jerusalem, located beyond the Israeli separation barrier and characterized by dense urban development and complex administrative status.

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_69f34989871c81908682e22a2fe4b829 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6fae822548190b5109528247b5be6 completed May 3, 2026, 7:36 a.m.
NED1 Entity disambiguation (via context triple) batch_6a365c7948a48190a52fe026d801c240 completed June 20, 2026, 9:25 a.m.
NEDg Description generation batch_6a365d90c1088190a7398e8ed30486e5 completed June 20, 2026, 9:29 a.m.
NED2 Entity disambiguation (via description) batch_6a365e46ab788190a9339c42340cccba completed June 20, 2026, 9:32 a.m.
Created at: May 1, 2026, 1:44 a.m.