Triple

T1036920
Position Surface form Disambiguated ID Type / Status
Subject Eric M. Taylor Center E22383 entity
Predicate formerName P65 FINISHED
Object CIFM
CIFM was the former name of the Eric M. Taylor Center, a correctional facility on Rikers Island in New York City.
 E122124 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: CIFM | Statement: [Eric M. Taylor Center, formerName, CIFM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CIFM
Context triple: [Eric M. Taylor Center, formerName, CIFM]
  • A. CAF
    CAF is a Spanish multinational company that designs and manufactures railway vehicles and related transport equipment used by metro systems worldwide.
  • B. CAF
    CAF is the Confederation of African Football, the governing body for association football in Africa and one of FIFA’s six continental confederations.
  • C. CAF
    CAF is the commonly used acronym for the Canadian Armed Forces, the unified military organization responsible for defending Canada and supporting international peace and security operations.
  • D. CEF
    CEF is the abbreviation for the Canadian Expeditionary Force, the field force of the Canadian Army raised for service overseas during the First World War.
  • E. CME
    CME is a major U.S.-based financial and commodity derivatives exchange known for trading futures and options on interest rates, equity indexes, foreign exchange, energy, and agricultural products.
  • 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: CIFM
Triple: [Eric M. Taylor Center, formerName, CIFM]
Generated description
CIFM was the former name of the Eric M. Taylor Center, a correctional facility on Rikers Island in New York City.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CIFM
Target entity description: CIFM was the former name of the Eric M. Taylor Center, a correctional facility on Rikers Island in New York City.
  • A. CAF
    CAF is a Spanish multinational company that designs and manufactures railway vehicles and related transport equipment used by metro systems worldwide.
  • B. CAF
    CAF is the Confederation of African Football, the governing body for association football in Africa and one of FIFA’s six continental confederations.
  • C. CAF
    CAF is the commonly used acronym for the Canadian Armed Forces, the unified military organization responsible for defending Canada and supporting international peace and security operations.
  • D. CEF
    CEF is the abbreviation for the Canadian Expeditionary Force, the field force of the Canadian Army raised for service overseas during the First World War.
  • E. CME
    CME is a major U.S.-based financial and commodity derivatives exchange known for trading futures and options on interest rates, equity indexes, foreign exchange, energy, and agricultural products.
  • 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_69a493d848848190aed4011b34b2e8d3 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b82a1014819085bfc077e24c9742 completed March 1, 2026, 10:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac3bc378fc8190846d5ffce73371dd completed March 7, 2026, 2:52 p.m.
NEDg Description generation batch_69ac3df28858819091c594a9cb2aab07 completed March 7, 2026, 3:02 p.m.
NED2 Entity disambiguation (via description) batch_69ac3e5b716c8190b95fde14ee6c434a completed March 7, 2026, 3:03 p.m.
Created at: March 1, 2026, 7:41 p.m.