Triple

T31945252
Position Surface form Disambiguated ID Type / Status
Subject H 133 E815632 entity
Predicate workSubject P7040 FINISHED
Object Aeneas in Carthage
Aeneas in Carthage is a classical mythological episode depicting the Trojan hero’s sojourn and tragic love affair with Queen Dido during his fated journey to found Rome.
E1985103 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: Aeneas in Carthage | Statement: [H 133, workSubject, Aeneas in Carthage]
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: Aeneas in Carthage
Triple: [H 133, workSubject, Aeneas in Carthage]
Generated description
Aeneas in Carthage is a classical mythological episode depicting the Trojan hero’s sojourn and tragic love affair with Queen Dido during his fated journey to found Rome.

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_69f348f42d188190a33fc8d20ec50517 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b27930d881909d5bef056bf5e7e5 completed May 3, 2026, 2:27 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2e8a484aa48190a02fa1d469a1ed15 completed June 14, 2026, 11:02 a.m.
NEDg Description generation batch_6a2e8b0d7b9881909941c614281a6c05 completed June 14, 2026, 11:05 a.m.
NED2 Entity disambiguation (via description) batch_6a2e8c005eb48190a28f4f07ad7c70af completed June 14, 2026, 11:09 a.m.
Created at: May 1, 2026, 12:06 a.m.