Triple

T7937940
Position Surface form Disambiguated ID Type / Status
Subject OpenStack E184327 entity
Predicate component P35 FINISHED
Object Monasca
Monasca is an OpenStack project that provides a scalable, multi-tenant monitoring-as-a-service solution for metrics, logs, and alarms in cloud environments.
 E699731 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: Monasca | Statement: [OpenStack, component, Monasca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Monasca
Context triple: [OpenStack, component, Monasca]
  • A. Antistia
    Antistia was the first wife of the Roman general and statesman Pompey the Great, whom he married early in his political career.
  • B. Mesaoria
    Mesaoria is the central plain of Cyprus, known for its fertile agricultural land and its role as a key geographical and historical region of the island.
  • C. Daphni
    Daphni is an area near Athens in Greece known for its historic monastery and its location along the ancient route between Athens and Eleusis.
  • D. Egrisi
    Egrisi was a medieval Georgian kingdom that emerged as a successor to ancient Colchis in the western Caucasus region.
  • E. Limonia
    Limonia is a small genus of flowering plants in the citrus family, best known for species like the wood-apple that produce hard-shelled, aromatic fruits.
  • 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: Monasca
Triple: [OpenStack, component, Monasca]
Generated description
Monasca is an OpenStack project that provides a scalable, multi-tenant monitoring-as-a-service solution for metrics, logs, and alarms in cloud environments.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Monasca
Target entity description: Monasca is an OpenStack project that provides a scalable, multi-tenant monitoring-as-a-service solution for metrics, logs, and alarms in cloud environments.
  • A. Antistia
    Antistia was the first wife of the Roman general and statesman Pompey the Great, whom he married early in his political career.
  • B. Mesaoria
    Mesaoria is the central plain of Cyprus, known for its fertile agricultural land and its role as a key geographical and historical region of the island.
  • C. Daphni
    Daphni is an area near Athens in Greece known for its historic monastery and its location along the ancient route between Athens and Eleusis.
  • D. Egrisi
    Egrisi was a medieval Georgian kingdom that emerged as a successor to ancient Colchis in the western Caucasus region.
  • E. Limonia
    Limonia is a small genus of flowering plants in the citrus family, best known for species like the wood-apple that produce hard-shelled, aromatic fruits.
  • 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_69ca8290c21c8190906a5ca6fe2b03c4 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3aef2394819086eea1f6ab117aed completed March 31, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5c0a96ac819099ad30fb925eb329 completed March 31, 2026, 5:30 a.m.
NEDg Description generation batch_69cb7634f4dc8190b5e537f24bccd651 completed March 31, 2026, 7:22 a.m.
NED2 Entity disambiguation (via description) batch_69cbb67e77a48190b93c6ba61becfac4 completed March 31, 2026, 11:56 a.m.
Created at: March 30, 2026, 5:08 p.m.