Triple

T317680
Position Surface form Disambiguated ID Type / Status
Subject GMC Sierra E7742 entity
Predicate hasTrimLevel P2393 FINISHED
Object SLT
SLT is a well-equipped, mid-to-upper trim level commonly associated with GMC trucks and SUVs, offering upgraded comfort, technology, and appearance features.
 E40911 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: SLT | Statement: [GMC Sierra, hasTrimLevel, SLT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SLT
Context triple: [GMC Sierra, hasTrimLevel, SLT]
  • A. SLD
    SLD was a particle physics experiment at the SLAC Linear Collider that made precision measurements of electroweak interactions, including properties of the Z boson.
  • B. SLV
    SLV is the three-letter ISO 3166-1 alpha-3 country code assigned to El Salvador.
  • C. SLC
    SLC is the three-letter IATA airport code for Salt Lake City International Airport, a major air travel hub serving Salt Lake City, Utah.
  • D. STLAM
    STLAM is the stock ticker symbol for Stellantis, a multinational automotive manufacturer formed from the merger of Fiat Chrysler Automobiles and PSA Group.
  • E. CLT
    CLT is a fundamental statistical principle stating that the sum or average of many independent, identically distributed random variables tends to follow a normal distribution, regardless of the original distribution.
  • 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: SLT
Triple: [GMC Sierra, hasTrimLevel, SLT]
Generated description
SLT is a well-equipped, mid-to-upper trim level commonly associated with GMC trucks and SUVs, offering upgraded comfort, technology, and appearance features.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SLT
Target entity description: SLT is a well-equipped, mid-to-upper trim level commonly associated with GMC trucks and SUVs, offering upgraded comfort, technology, and appearance features.
  • A. SLD
    SLD was a particle physics experiment at the SLAC Linear Collider that made precision measurements of electroweak interactions, including properties of the Z boson.
  • B. SLV
    SLV is the three-letter ISO 3166-1 alpha-3 country code assigned to El Salvador.
  • C. SLC
    SLC is the three-letter IATA airport code for Salt Lake City International Airport, a major air travel hub serving Salt Lake City, Utah.
  • D. STLAM
    STLAM is the stock ticker symbol for Stellantis, a multinational automotive manufacturer formed from the merger of Fiat Chrysler Automobiles and PSA Group.
  • E. CLT
    CLT is a fundamental statistical principle stating that the sum or average of many independent, identically distributed random variables tends to follow a normal distribution, regardless of the original distribution.
  • 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_69a2e7e7af7881908890039d6be4e9b8 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ee016c408190beab4009653524db completed Feb. 28, 2026, 1:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3c8b8d7d88190b43f7b6b0289445f completed March 1, 2026, 5:03 a.m.
NEDg Description generation batch_69a3c964b7a48190afa7cada4a499739 completed March 1, 2026, 5:06 a.m.
NED2 Entity disambiguation (via description) batch_69a3c9bc3eec81909e6d1b7af6cf7d58 completed March 1, 2026, 5:08 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.