Triple

T30376753
Position Surface form Disambiguated ID Type / Status
Subject Njimi E772711 entity
Predicate connectedTo P37 FINISHED
Object Tripoli
Tripoli is the capital and largest city of Libya, a major Mediterranean port with a long history as a center of trade and culture in North Africa.
E12108 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: Tripoli | Statement: [Njimi, connectedTo, Tripoli]
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: Tripoli
Triple: [Njimi, connectedTo, Tripoli]
Generated description
Tripoli is the capital and largest city of Libya, a major Mediterranean port with a long history as a center of trade and culture in North Africa.

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_69f2248e3444819081b05712dc6873de completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68513cbf881908ec5f924484b19b9 completed May 2, 2026, 11:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a278925c79881908688188ed32a4734 completed June 9, 2026, 3:31 a.m.
NEDg Description generation batch_6a278a5d184081908fbaf650cb44e2b7 completed June 9, 2026, 3:37 a.m.
NED2 Entity disambiguation (via description) batch_6a278cda6ab8819097cd6e2f0b1124c1 completed June 9, 2026, 3:47 a.m.
Created at: April 29, 2026, 8 p.m.