Triple

T2058363
Position Surface form Disambiguated ID Type / Status
Subject MIT Laboratory for Information and Decision Systems E45729 entity
Predicate shortName P43 FINISHED
Object LIDS
LIDS is a research laboratory at MIT focused on advancing the theory and application of information and decision systems, including areas like control, communications, and machine learning.
 E228293 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: LIDS | Statement: [MIT Laboratory for Information and Decision Systems, shortName, LIDS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LIDS
Context triple: [MIT Laboratory for Information and Decision Systems, shortName, LIDS]
  • A. LYD
    LYD is the ISO 4217 currency code for the Libyan dinar, the official currency of Libya.
  • B. LYD
    LYD is the station code for Lyon-Part-Dieu, a major high-speed rail hub and one of the main railway stations in Lyon, France.
  • C. LIMC
    LIMC is the ICAO airport code for Milan Malpensa Airport, a major international airport serving the Milan metropolitan area in Italy.
  • D. LCH
    LCH is a leading global clearing house that provides central counterparty clearing services for a wide range of financial markets and asset classes.
  • E. LIM
    LIM is the IATA airport code for Jorge Chávez International Airport, the main international gateway serving Lima, Peru.
  • 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: LIDS
Triple: [MIT Laboratory for Information and Decision Systems, shortName, LIDS]
Generated description
LIDS is a research laboratory at MIT focused on advancing the theory and application of information and decision systems, including areas like control, communications, and machine learning.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LIDS
Target entity description: LIDS is a research laboratory at MIT focused on advancing the theory and application of information and decision systems, including areas like control, communications, and machine learning.
  • A. LYD
    LYD is the ISO 4217 currency code for the Libyan dinar, the official currency of Libya.
  • B. LYD
    LYD is the station code for Lyon-Part-Dieu, a major high-speed rail hub and one of the main railway stations in Lyon, France.
  • C. LIMC
    LIMC is the ICAO airport code for Milan Malpensa Airport, a major international airport serving the Milan metropolitan area in Italy.
  • D. LCH
    LCH is a leading global clearing house that provides central counterparty clearing services for a wide range of financial markets and asset classes.
  • E. LIM
    LIM is the IATA airport code for Jorge Chávez International Airport, the main international gateway serving Lima, Peru.
  • 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_69a8891a19508190a12ef1e192308dcb completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb9ae0130819089f7d62005466a45 completed March 7, 2026, 5:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae2014da048190902b2a23574d34ef completed March 9, 2026, 1:19 a.m.
NEDg Description generation batch_69ae20dff3c48190943a913c63247537 completed March 9, 2026, 1:22 a.m.
NED2 Entity disambiguation (via description) batch_69ae21465d048190a1ee3a52c96ee37d completed March 9, 2026, 1:24 a.m.
Created at: March 4, 2026, 7:40 p.m.