Triple

T1738369
Position Surface form Disambiguated ID Type / Status
Subject Tara Lipinski E37971 entity
Predicate familyName P18 FINISHED
Object Lipinski
Lipinski is a Polish-origin surname borne by various notable individuals in fields such as sports, music, and politics.
 E193417 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: Lipinski | Statement: [Tara Lipinski, familyName, Lipinski]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lipinski
Context triple: [Tara Lipinski, familyName, Lipinski]
  • A. Versonnex
    Versonnex is a small commune in the Ain department of eastern France, located near the Swiss border in the Pays de Gex region.
  • B. Fremulon
    Fremulon is a television production company founded by Michael Schur, best known for producing acclaimed comedy series such as Brooklyn Nine-Nine.
  • C. Lipikar
    Lipikar is La Roche-Posay’s dermatological body-care line formulated to hydrate, protect, and soothe dry to very dry and sensitive skin.
  • D. Schlick
    Schlick is a German surname most notably associated with Moritz Schlick, a leading philosopher and founder of the Vienna Circle.
  • E. Vivanco
    Vivanco is a Spanish-language surname of likely Iberian origin borne by various notable individuals.
  • 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: Lipinski
Triple: [Tara Lipinski, familyName, Lipinski]
Generated description
Lipinski is a Polish-origin surname borne by various notable individuals in fields such as sports, music, and politics.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lipinski
Target entity description: Lipinski is a Polish-origin surname borne by various notable individuals in fields such as sports, music, and politics.
  • A. Versonnex
    Versonnex is a small commune in the Ain department of eastern France, located near the Swiss border in the Pays de Gex region.
  • B. Fremulon
    Fremulon is a television production company founded by Michael Schur, best known for producing acclaimed comedy series such as Brooklyn Nine-Nine.
  • C. Lipikar
    Lipikar is La Roche-Posay’s dermatological body-care line formulated to hydrate, protect, and soothe dry to very dry and sensitive skin.
  • D. Schlick
    Schlick is a German surname most notably associated with Moritz Schlick, a leading philosopher and founder of the Vienna Circle.
  • E. Vivanco
    Vivanco is a Spanish-language surname of likely Iberian origin borne by various notable individuals.
  • 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_69a8861cc6ac8190ac0b2e31ccf62851 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa63c35aec8190b5c19ace5524173f completed March 6, 2026, 5:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad8b03303c8190a301dca327bf9f47 completed March 8, 2026, 2:43 p.m.
NEDg Description generation batch_69ad957e9a6c81909d52bf2def797526 completed March 8, 2026, 3:27 p.m.
NED2 Entity disambiguation (via description) batch_69ad97b6c03881909f278594e800c0f5 completed March 8, 2026, 3:37 p.m.
Created at: March 4, 2026, 7:30 p.m.