Triple

T11484677
Position Surface form Disambiguated ID Type / Status
Subject Service Contract Act E272243 entity
Predicate shortName P43 FINISHED
Object SCA
SCA is the common abbreviation for the Service Contract Act, a U.S. federal law that sets wage and benefit standards for employees working on government service contracts.
 E928680 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: SCA | Statement: [Service Contract Act, shortName, SCA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SCA
Context triple: [Service Contract Act, shortName, SCA]
  • A. SCA
    SCA is the National Rail station code for Scarborough railway station in North Yorkshire, England.
  • B. SCA
    SCA is a software composition analysis solution that identifies and manages vulnerabilities and license risks in open-source components used within applications.
  • C. SCA
    SCA is a U.S. federal law that governs the privacy and disclosure of stored electronic communications and related data held by service providers.
  • D. SCA
    The SCA is South Africa’s highest court of appeal for non-constitutional matters, based in Bloemfontein.
  • E. SCA
    SCA is the commonly used abbreviation for Hay’at Qanāt as-Suways, the authority responsible for managing and operating Egypt’s Suez Canal.
  • 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: SCA
Triple: [Service Contract Act, shortName, SCA]
Generated description
SCA is the common abbreviation for the Service Contract Act, a U.S. federal law that sets wage and benefit standards for employees working on government service contracts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SCA
Target entity description: SCA is the common abbreviation for the Service Contract Act, a U.S. federal law that sets wage and benefit standards for employees working on government service contracts.
  • A. SCA
    SCA is the National Rail station code for Scarborough railway station in North Yorkshire, England.
  • B. SCA
    SCA is a U.S. federal law that governs the privacy and disclosure of stored electronic communications and related data held by service providers.
  • C. SCA
    SCA is a software composition analysis solution that identifies and manages vulnerabilities and license risks in open-source components used within applications.
  • D. SCA
    The SCA is South Africa’s highest court of appeal for non-constitutional matters, based in Bloemfontein.
  • E. SCA
    SCA is the commonly used abbreviation for Hay’at Qanāt as-Suways, the authority responsible for managing and operating Egypt’s Suez Canal.
  • 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_69d6aae1b09881909ce2ded3fa0c14fa completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d85a1ea00c8190b42cdc13a6bc61c3 completed April 10, 2026, 2:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69e60451a89081909f9534fee6cb809f completed April 20, 2026, 10:47 a.m.
NEDg Description generation batch_69e610a5ea0481908169c58dc0831b76 completed April 20, 2026, 11:40 a.m.
NED2 Entity disambiguation (via description) batch_69e6182b06f88190ab36d976ac989019 completed April 20, 2026, 12:12 p.m.
Created at: April 8, 2026, 9:36 p.m.