Triple

T2620477
Position Surface form Disambiguated ID Type / Status
Subject Jenny Holzer E58995 entity
Predicate notableWork P4 FINISHED
Object For SAAM
For SAAM is a text-based installation artwork by Jenny Holzer that uses her signature LED display format to present thought-provoking, politically charged language within a museum context.
 E284066 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: For SAAM | Statement: [Jenny Holzer, notableWork, For SAAM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: For SAAM
Context triple: [Jenny Holzer, notableWork, For SAAM]
  • A. SAA
    SAA is the ICAO airline designator for South African Airways, the flag carrier airline of South Africa.
  • B. SAMO
    SAMO was the graffiti tag and artistic persona used by Jean-Michel Basquiat in late-1970s New York City, known for its cryptic, poetic street art.
  • C. SA2
    SA2 is a 3GPP working group responsible for defining the overall system architecture and functional specifications of mobile communication networks.
  • D. SA3
    SA3 is the 3GPP security working group responsible for specifying and evolving security architecture and mechanisms across mobile communication standards.
  • E. SAM
    SAM is an analytical laboratory aboard NASA's Curiosity rover that studies Martian rocks, soil, and atmosphere to determine their chemical and organic composition.
  • 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: For SAAM
Triple: [Jenny Holzer, notableWork, For SAAM]
Generated description
For SAAM is a text-based installation artwork by Jenny Holzer that uses her signature LED display format to present thought-provoking, politically charged language within a museum context.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: For SAAM
Target entity description: For SAAM is a text-based installation artwork by Jenny Holzer that uses her signature LED display format to present thought-provoking, politically charged language within a museum context.
  • A. SAA
    SAA is the ICAO airline designator for South African Airways, the flag carrier airline of South Africa.
  • B. SAMO
    SAMO was the graffiti tag and artistic persona used by Jean-Michel Basquiat in late-1970s New York City, known for its cryptic, poetic street art.
  • C. SA2
    SA2 is a 3GPP working group responsible for defining the overall system architecture and functional specifications of mobile communication networks.
  • D. SA3
    SA3 is the 3GPP security working group responsible for specifying and evolving security architecture and mechanisms across mobile communication standards.
  • E. SAM
    SAM is an analytical laboratory aboard NASA's Curiosity rover that studies Martian rocks, soil, and atmosphere to determine their chemical and organic composition.
  • 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_69ab4ac558388190962492cd2e1b0ce6 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd897acb481909a976b70304cc30e completed March 7, 2026, 7:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69af908ec0cc8190ab8feb8f237eac4b completed March 10, 2026, 3:31 a.m.
NEDg Description generation batch_69af91a3b4588190acfb360dac6e5ce0 completed March 10, 2026, 3:36 a.m.
NED2 Entity disambiguation (via description) batch_69af920b7fcc8190b5a34c7c626a1c5d completed March 10, 2026, 3:37 a.m.
Created at: March 6, 2026, 9:50 p.m.