Triple

T23881861
Position Surface form Disambiguated ID Type / Status
Subject Abdullah Azzam E600223 entity
Predicate citizenship P2 FINISHED
Object Jordan
Jordan is a Middle Eastern country located at the crossroads of Asia, Africa, and Europe, known for its political stability, historical sites like Petra, and significant role in regional geopolitics.
E11658 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: Jordan | Statement: [Abdullah Azzam, citizenship, Jordan]
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: Jordan
Triple: [Abdullah Azzam, citizenship, Jordan]
Generated description
Jordan is a Middle Eastern country located at the crossroads of Asia, Africa, and Europe, known for its political stability, historical sites like Petra, and significant role in regional geopolitics.

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_69e295318e148190b9979d8fc02e168f completed April 17, 2026, 8:16 p.m.
NER Named-entity recognition batch_69f1cc05e4d48190864fc47bdffa4ca9 completed April 29, 2026, 9:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f699c7e6c8190a8f5ec0dc7beea69 completed May 21, 2026, 8:22 p.m.
NEDg Description generation batch_6a0f6d44a56081909fb094eade37e589 completed May 21, 2026, 8:38 p.m.
NED2 Entity disambiguation (via description) batch_6a0f6df970a08190b1d3959a39b30233 completed May 21, 2026, 8:41 p.m.
Created at: April 17, 2026, 8:24 p.m.