Triple

T7686498
Position Surface form Disambiguated ID Type / Status
Subject MIT Center for Advanced Urbanism E174129 entity
Predicate abbreviation P43 FINISHED
Object CAU
CAU is the MIT Center for Advanced Urbanism, a research hub focused on innovative design and policy solutions for contemporary urban challenges.
 E681690 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: CAU | Statement: [MIT Center for Advanced Urbanism, abbreviation, CAU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CAU
Context triple: [MIT Center for Advanced Urbanism, abbreviation, CAU]
  • A. CUA
    CUA is a joint MIT–Harvard research center focused on the study of ultracold atomic physics and quantum phenomena.
  • B. CUA
    CUA is the ICAO airline designator for China United Airlines, a Chinese domestic carrier based in Beijing.
  • C. ACU
    ACU is the standard camouflage field uniform worn by soldiers of the United States Army.
  • D. ACU
    ACU (the Association of Commonwealth Universities) is an international network of higher education institutions from Commonwealth countries that promotes collaboration, academic excellence, and educational development.
  • E. UCA
    UCA is the Unicode Collation Algorithm, a Unicode standard that defines a language-independent method for ordering and comparing Unicode text.
  • 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: CAU
Triple: [MIT Center for Advanced Urbanism, abbreviation, CAU]
Generated description
CAU is the MIT Center for Advanced Urbanism, a research hub focused on innovative design and policy solutions for contemporary urban challenges.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CAU
Target entity description: CAU is the MIT Center for Advanced Urbanism, a research hub focused on innovative design and policy solutions for contemporary urban challenges.
  • A. CUA
    CUA is a joint MIT–Harvard research center focused on the study of ultracold atomic physics and quantum phenomena.
  • B. CUA
    CUA is the ICAO airline designator for China United Airlines, a Chinese domestic carrier based in Beijing.
  • C. ACU
    ACU is the standard camouflage field uniform worn by soldiers of the United States Army.
  • D. ACU
    ACU (the Association of Commonwealth Universities) is an international network of higher education institutions from Commonwealth countries that promotes collaboration, academic excellence, and educational development.
  • E. UCA
    UCA is the Unicode Collation Algorithm, a Unicode standard that defines a language-independent method for ordering and comparing Unicode text.
  • 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_69c6995840408190a19de6c51090f46f completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7022352088190b2510d5fac55864f completed March 27, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8a25c2a308190908ffdd2f0b7262f completed March 29, 2026, 3:54 a.m.
NEDg Description generation batch_69c8a37c995881908c71791c6cc002f3 completed March 29, 2026, 3:58 a.m.
NED2 Entity disambiguation (via description) batch_69c8a3fe63a4819086bcb5f80cdbd30b completed March 29, 2026, 4:01 a.m.
Created at: March 27, 2026, 4:02 p.m.