Triple

T3703769
Position Surface form Disambiguated ID Type / Status
Subject Washington State Cougars E80841 entity
Predicate hasStudentSectionName P13219 FINISHED
Object ZZU CRU
ZZU CRU is the official, highly spirited student fan section that supports Washington State University Cougars athletic teams.
E382358 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: ZZU CRU | Statement: [Washington State Cougars, hasStudentSectionName, ZZU CRU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ZZU CRU
Context triple: [Washington State Cougars, hasStudentSectionName, ZZU CRU]
  • A. ZTU
    ZTU is the IATA station code assigned to a specific passenger rail station in Miami, Florida, used for ticketing and travel logistics.
  • B. ZUEL
    ZUEL is a prominent Chinese university specializing in economics, law, and related social sciences, located in Wuhan, Hubei Province.
  • C. ZCHS
    ZCHS is a public high school serving the Zionsville, Indiana community, known for its strong academics and extracurricular programs.
  • D. ZUE
    ZUE is the railway station code for Zürich Hauptbahnhof, Switzerland’s largest and busiest train station and a major European rail hub.
  • E. SCUT
    SCUT is a major public research university in Guangzhou, China, known for its strong engineering, technology, and applied science programs.
  • 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: ZZU CRU
Triple: [Washington State Cougars, hasStudentSectionName, ZZU CRU]
Generated description
ZZU CRU is the official, highly spirited student fan section that supports Washington State University Cougars athletic teams.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: ZZU CRU
Target entity description: ZZU CRU is the official, highly spirited student fan section that supports Washington State University Cougars athletic teams.
  • A. ZTU
    ZTU is the IATA station code assigned to a specific passenger rail station in Miami, Florida, used for ticketing and travel logistics.
  • B. ZUEL
    ZUEL is a prominent Chinese university specializing in economics, law, and related social sciences, located in Wuhan, Hubei Province.
  • C. ZCHS
    ZCHS is a public high school serving the Zionsville, Indiana community, known for its strong academics and extracurricular programs.
  • D. ZUE
    ZUE is the railway station code for Zürich Hauptbahnhof, Switzerland’s largest and busiest train station and a major European rail hub.
  • E. SCUT
    SCUT is a major public research university in Guangzhou, China, known for its strong engineering, technology, and applied science programs.
  • 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_69ad8b1793888190a5f70e4b21dc05a1 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adc54aaac88190b775dba2513b6d4a completed March 8, 2026, 6:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4cdf822348190bf95f7d119c6265a completed March 14, 2026, 2:54 a.m.
NEDg Description generation batch_69b4d1f486c48190b0206beb7f913eb0 completed March 14, 2026, 3:11 a.m.
NED2 Entity disambiguation (via description) batch_69b4d29d8b688190b6ece3d8d65bc16c completed March 14, 2026, 3:14 a.m.
Created at: March 8, 2026, 3:33 p.m.