Triple

T8505109
Position Surface form Disambiguated ID Type / Status
Subject BOK Center E201313 entity
Predicate hasNickName P39 FINISHED
Object BOK
BOK is the commonly used nickname for the BOK Center, a major multi-purpose arena in Tulsa, Oklahoma.
E739351 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: BOK | Statement: [BOK Center, hasNickName, BOK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BOK
Context triple: [BOK Center, hasNickName, BOK]
  • A. BOK
    BOK is the commonly used abbreviation for the Bank of Korea, South Korea’s central bank responsible for monetary policy and financial stability.
  • B. BOK
    BOK is the station code for Berlin Ostkreuz, a major railway interchange in Berlin, Germany.
  • C. BOL
    BOL is the three-letter ISO 3166-1 alpha-3 country code assigned to Bolivia.
  • D. Bokn
    Bokn is a small island municipality in southwestern Norway known for its coastal landscape and location in Rogaland county.
  • E. BOCHK
    BOCHK is the commonly used abbreviation for Bank of China (Hong Kong), a major commercial banking group based in Hong Kong.
  • 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: BOK
Triple: [BOK Center, hasNickName, BOK]
Generated description
BOK is the commonly used nickname for the BOK Center, a major multi-purpose arena in Tulsa, Oklahoma.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: BOK
Target entity description: BOK is the commonly used nickname for the BOK Center, a major multi-purpose arena in Tulsa, Oklahoma.
  • A. BOK
    BOK is the commonly used abbreviation for the Bank of Korea, South Korea’s central bank responsible for monetary policy and financial stability.
  • B. BOK
    BOK is the station code for Berlin Ostkreuz, a major railway interchange in Berlin, Germany.
  • C. BOL
    BOL is the three-letter ISO 3166-1 alpha-3 country code assigned to Bolivia.
  • D. Bokn
    Bokn is a small island municipality in southwestern Norway known for its coastal landscape and location in Rogaland county.
  • E. BOCHK
    BOCHK is the commonly used abbreviation for Bank of China (Hong Kong), a major commercial banking group based in Hong Kong.
  • 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_69ca831fe47c8190b5c57b456d2aefa0 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe5d8b7208190b199c56bf366c692 completed March 31, 2026, 3:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce4e3037e4819090677c7dc607e8f2 completed April 2, 2026, 11:08 a.m.
NEDg Description generation batch_69ce4ff88ff48190a5641635187a9e4f completed April 2, 2026, 11:16 a.m.
NED2 Entity disambiguation (via description) batch_69ce50fd3150819097562093bee78a6d completed April 2, 2026, 11:20 a.m.
Created at: March 30, 2026, 6:14 p.m.