Triple

T30107724
Position Surface form Disambiguated ID Type / Status
Subject Poem 85 (Odi et amo) E765176 entity
Predicate alsoKnownAs P39 FINISHED
Object Catullus 85
Catullus 85 is a famous two-line Latin poem by the Roman poet Catullus that encapsulates the torment of conflicted love with the words "odi et amo" ("I hate and I love").
E1913482 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: Catullus 85 | Statement: [Poem 85 (Odi et amo), alsoKnownAs, Catullus 85]
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: Catullus 85
Triple: [Poem 85 (Odi et amo), alsoKnownAs, Catullus 85]
Generated description
Catullus 85 is a famous two-line Latin poem by the Roman poet Catullus that encapsulates the torment of conflicted love with the words "odi et amo" ("I hate and I love").

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_69f22475ad7c8190be7f9541044a0bbb completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67dbc4278819088f599a06c490287 completed May 2, 2026, 10:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2789222d2c81909a0fd565824386c6 completed June 9, 2026, 3:31 a.m.
NEDg Description generation batch_6a2789db54048190ab54d623ce1d4e2a completed June 9, 2026, 3:34 a.m.
NED2 Entity disambiguation (via description) batch_6a278a76f450819095acd3e2b23d2b73 completed June 9, 2026, 3:37 a.m.
Created at: April 29, 2026, 7:09 p.m.