Triple

T1321434
Position Surface form Disambiguated ID Type / Status
Subject Opole E28226 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object OPO
OPO is the vehicle registration code assigned to the Polish city of Opole.
 E150880 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: OPO | Statement: [Opole, vehicleRegistrationCode, OPO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: OPO
Context triple: [Opole, vehicleRegistrationCode, OPO]
  • A. 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.
  • B. O.P.
    O.P. is a common abbreviation that can stand for various phrases such as “original poster,” “original post,” or “out of print,” depending on the context in which it is used.
  • C. OPAL
    OPAL was one of the major particle physics experiments at CERN’s Large Electron–Positron Collider, designed to study electron-positron collisions and probe the Standard Model.
  • D. EOP
    EOP is the collective group of offices and agencies that directly support the President of the United States in carrying out executive responsibilities and policy initiatives.
  • E. OSO
    OSO is the commonly used abbreviation for the Office of SIGINT Operations, a signals intelligence unit within the U.S. National Security Agency.
  • 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: OPO
Triple: [Opole, vehicleRegistrationCode, OPO]
Generated description
OPO is the vehicle registration code assigned to the Polish city of Opole.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: OPO
Target entity description: OPO is the vehicle registration code assigned to the Polish city of Opole.
  • A. 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.
  • B. O.P.
    O.P. is a common abbreviation that can stand for various phrases such as “original poster,” “original post,” or “out of print,” depending on the context in which it is used.
  • C. OPAL
    OPAL was one of the major particle physics experiments at CERN’s Large Electron–Positron Collider, designed to study electron-positron collisions and probe the Standard Model.
  • D. EOP
    EOP is the collective group of offices and agencies that directly support the President of the United States in carrying out executive responsibilities and policy initiatives.
  • E. OSO
    OSO is the commonly used abbreviation for the Office of SIGINT Operations, a signals intelligence unit within the U.S. National Security Agency.
  • 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_69a498540a2481909e807a762280d3ba completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c19932888190a3d45871e84f112e completed March 1, 2026, 10:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69acbaf6a6d08190b8a30c2c64f15f59 completed March 7, 2026, 11:55 p.m.
NEDg Description generation batch_69acbbd8b6b881908412e5ab5d9baf79 completed March 7, 2026, 11:59 p.m.
NED2 Entity disambiguation (via description) batch_69acbd0dcf74819093b5985b0f3bc8a2 completed March 8, 2026, 12:04 a.m.
Created at: March 1, 2026, 7:55 p.m.