Triple

T2504745
Position Surface form Disambiguated ID Type / Status
Subject Province of Como E52551 entity
Predicate contains P35 FINISHED
Object Erba
Erba is a town in the Lombardy region of northern Italy, situated near Lake Como and known for its scenic surroundings and local industry.
 E271830 NE FINISHED

How this triple was built (4 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: Erba | Statement: [Province of Como, contains, Erba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Erba
Context triple: [Province of Como, contains, Erba]
  • A. Gebal
    Gebal is the ancient name of the Phoenician coastal city later known as Byblos, one of the oldest continuously inhabited cities in the world.
  • B. Iadera
    Iadera is the ancient Roman and medieval Latin name for the coastal city now known as Zadar in Croatia.
  • C. Ráquira
    Ráquira is a Colombian town renowned for its traditional pottery, colorful handicrafts, and vibrant colonial architecture.
  • D. Errana
    Errana is a medieval Telugu poet known for collaborating on and continuing the composition of the Telugu Mahabharata.
  • E. Idumea
    Idumea was an ancient region south of Judea, inhabited by the Edomites and later integrated into the Hasmonean and Herodian Jewish realms.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Erba
Triple: [Province of Como, contains, Erba]
Generated description
Erba is a town in the Lombardy region of northern Italy, situated near Lake Como and known for its scenic surroundings and local industry.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Erba
Target entity description: Erba is a town in the Lombardy region of northern Italy, situated near Lake Como and known for its scenic surroundings and local industry.
  • A. Gebal
    Gebal is the ancient name of the Phoenician coastal city later known as Byblos, one of the oldest continuously inhabited cities in the world.
  • B. Iadera
    Iadera is the ancient Roman and medieval Latin name for the coastal city now known as Zadar in Croatia.
  • C. Ráquira
    Ráquira is a Colombian town renowned for its traditional pottery, colorful handicrafts, and vibrant colonial architecture.
  • D. Errana
    Errana is a medieval Telugu poet known for collaborating on and continuing the composition of the Telugu Mahabharata.
  • E. Idumea
    Idumea was an ancient region south of Judea, inhabited by the Edomites and later integrated into the Hasmonean and Herodian Jewish realms.
  • F. None of above. chosen

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_69ab4957b3a88190adf968ae0c1b931c completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd1cd2db0819087d21ec49ffd9585 completed March 7, 2026, 7:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69af1fa57aa4819096578a5538973ec4 completed March 9, 2026, 7:29 p.m.
NEDg Description generation batch_69af203f7ca08190ba781891bd879192 completed March 9, 2026, 7:32 p.m.
NED2 Entity disambiguation (via description) batch_69af20cd13a88190a35bc1b74ad088ef completed March 9, 2026, 7:34 p.m.
Created at: March 6, 2026, 9:46 p.m.