Triple

T36714940
Position Surface form Disambiguated ID Type / Status
Subject Embassy of the United States in Amman E906889 entity
Predicate locatedInCountry P40 FINISHED
Object Jordan
Jordan is a Middle Eastern country on the east bank of the Jordan River, known for its political stability, ancient archaeological 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: [Embassy of the United States in Amman, locatedInCountry, 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: [Embassy of the United States in Amman, locatedInCountry, Jordan]
Generated description
Jordan is a Middle Eastern country on the east bank of the Jordan River, known for its political stability, ancient archaeological 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_69f76e73ad108190a5241585f2303e9a completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7c83f5960819089610ed39c839678 completed May 3, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3a3824428881909e79dfa8f1858bda completed June 23, 2026, 7:39 a.m.
NEDg Description generation batch_6a3a38a32c9481909b133bfd99520e50 completed June 23, 2026, 7:41 a.m.
NED2 Entity disambiguation (via description) batch_6a3a3a91ef8c819086b3b5633154063a completed June 23, 2026, 7:49 a.m.
Created at: May 3, 2026, 4:12 p.m.