Triple

T2055537
Position Surface form Disambiguated ID Type / Status
Subject Roman army E45664 entity
Predicate hasRank P337 FINISHED
Object optio
An optio was a junior officer in the Roman army who served as the deputy and second-in-command to a centurion within a legionary unit.
 E228784 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: optio | Statement: [Roman army, hasRank, optio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: optio
Context triple: [Roman army, hasRank, optio]
  • A. Opti
    Opti is a friendly, futuristic robot character that served as one of the official mascots of Expo 2020 Dubai.
  • B. Optimates
    The Optimates were a conservative political faction in the late Roman Republic that championed senatorial authority and traditional aristocratic privileges against popular reformers like Julius Caesar.
  • C. OPA
    OPA is a U.S. federal law enacted in 1990 that strengthens regulations and liability standards for preventing and responding to oil spills in navigable waters and shorelines.
  • D. OPO
    OPO is the vehicle registration code assigned to the Polish city of Opole.
  • E. OEI
    OEI is the Spanish-Portuguese acronym for the Organization of Ibero-American States, an international body that promotes cooperation in education, science, and culture among Ibero-American countries.
  • 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: optio
Triple: [Roman army, hasRank, optio]
Generated description
An optio was a junior officer in the Roman army who served as the deputy and second-in-command to a centurion within a legionary unit.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: optio
Target entity description: An optio was a junior officer in the Roman army who served as the deputy and second-in-command to a centurion within a legionary unit.
  • A. Opti
    Opti is a friendly, futuristic robot character that served as one of the official mascots of Expo 2020 Dubai.
  • B. Optimates
    The Optimates were a conservative political faction in the late Roman Republic that championed senatorial authority and traditional aristocratic privileges against popular reformers like Julius Caesar.
  • C. OPA
    OPA is a U.S. federal law enacted in 1990 that strengthens regulations and liability standards for preventing and responding to oil spills in navigable waters and shorelines.
  • D. OPO
    OPO is the vehicle registration code assigned to the Polish city of Opole.
  • E. OEI
    OEI is the Spanish-Portuguese acronym for the Organization of Ibero-American States, an international body that promotes cooperation in education, science, and culture among Ibero-American countries.
  • 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_69a8891a19508190a12ef1e192308dcb completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb9a9ce548190a5a3488fafb2e79e completed March 7, 2026, 5:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae200eb09881908bbfe47ebb62f55e completed March 9, 2026, 1:19 a.m.
NEDg Description generation batch_69ae20cb479c8190853d0d954af16887 completed March 9, 2026, 1:22 a.m.
NED2 Entity disambiguation (via description) batch_69ae21614e74819093617a355f0857c8 completed March 9, 2026, 1:24 a.m.
Created at: March 4, 2026, 7:40 p.m.