Triple

T31077776
Position Surface form Disambiguated ID Type / Status
Subject Vicus Iugarius E792013 entity
Predicate hasNameInLatin P9999 FINISHED
Object Vicus Iugarius
Vicus Iugarius was an ancient street in Rome that ran through the Forum Romanum, connecting important commercial and religious areas of the city.
E1945005 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: Vicus Iugarius | Statement: [Vicus Iugarius, hasNameInLatin, Vicus Iugarius]
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: Vicus Iugarius
Triple: [Vicus Iugarius, hasNameInLatin, Vicus Iugarius]
Generated description
Vicus Iugarius was an ancient street in Rome that ran through the Forum Romanum, connecting important commercial and religious areas of the city.

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_69f224ccdbbc81909b0cdb4cc2d70c7a completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f695bbbaa081909fb1aa003e864c08 completed May 3, 2026, 12:24 a.m.
NED1 Entity disambiguation (via context triple) batch_6a292b2627c48190a5dcf3b6f5cf0f7c completed June 10, 2026, 9:15 a.m.
NEDg Description generation batch_6a292d6a1fb0819095d6a3f07e5c2329 completed June 10, 2026, 9:24 a.m.
NED2 Entity disambiguation (via description) batch_6a292e38a7bc81908dc2261b06212031 completed June 10, 2026, 9:28 a.m.
Created at: April 29, 2026, 9:02 p.m.