Triple

T2440909
Position Surface form Disambiguated ID Type / Status
Subject Jordi Galí E53271 entity
Predicate hasAffiliation P467 FINISHED
Object CREI
CREI is a Barcelona-based research institute specializing in macroeconomics and international economics, closely linked to academic institutions such as Universitat Pompeu Fabra.
 E266783 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: CREI | Statement: [Jordi Galí, hasAffiliation, CREI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CREI
Context triple: [Jordi Galí, hasAffiliation, CREI]
  • A. CREST
    CREST is the UK’s central securities depository and electronic settlement system used to hold and settle trades in shares and other securities.
  • B. CRI
    CRI is the three-letter ISO 3166-1 alpha-3 country code assigned to Costa Rica.
  • C. CREEP
    CREEP was the informal name for U.S. President Richard Nixon’s 1972 re-election campaign organization, which became infamous for its central role in the Watergate scandal.
  • D. CrIS
    CrIS is a hyperspectral infrared sounder instrument used on NOAA’s Joint Polar Satellite System satellites to measure atmospheric temperature, moisture, and trace gases for weather forecasting and climate monitoring.
  • E. MIT/CRE
    MIT/CRE is the MIT Center for Real Estate, a leading academic hub for research and education in real estate finance, development, and innovation.
  • 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: CREI
Triple: [Jordi Galí, hasAffiliation, CREI]
Generated description
CREI is a Barcelona-based research institute specializing in macroeconomics and international economics, closely linked to academic institutions such as Universitat Pompeu Fabra.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CREI
Target entity description: CREI is a Barcelona-based research institute specializing in macroeconomics and international economics, closely linked to academic institutions such as Universitat Pompeu Fabra.
  • A. CREST
    CREST is the UK’s central securities depository and electronic settlement system used to hold and settle trades in shares and other securities.
  • B. CRI
    CRI is the three-letter ISO 3166-1 alpha-3 country code assigned to Costa Rica.
  • C. CREEP
    CREEP was the informal name for U.S. President Richard Nixon’s 1972 re-election campaign organization, which became infamous for its central role in the Watergate scandal.
  • D. CrIS
    CrIS is a hyperspectral infrared sounder instrument used on NOAA’s Joint Polar Satellite System satellites to measure atmospheric temperature, moisture, and trace gases for weather forecasting and climate monitoring.
  • E. MIT/CRE
    MIT/CRE is the MIT Center for Real Estate, a leading academic hub for research and education in real estate finance, development, and innovation.
  • 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_69ab495b6dac8190ac82661aa1452222 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abc9f94e388190b6e49d4f7bbb6697 completed March 7, 2026, 6:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69aef0b3f7188190911f2db0ef2200cc completed March 9, 2026, 4:09 p.m.
NEDg Description generation batch_69aef3752d6c8190b32d99418c0bfdc8 completed March 9, 2026, 4:21 p.m.
NED2 Entity disambiguation (via description) batch_69aef433a83c8190b20a3a278204badd completed March 9, 2026, 4:24 p.m.
Created at: March 6, 2026, 9:43 p.m.