Triple

T3731222
Position Surface form Disambiguated ID Type / Status
Subject Steve Prefontaine E79066 entity
Predicate nickname P55 FINISHED
Object Pre
Pre is the famous nickname of Steve Prefontaine, the iconic American middle- and long-distance runner known for his aggressive racing style and role in popularizing running in the 1970s.
 E384867 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: Pre | Statement: [Steve Prefontaine, nickname, Pre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Pre
Context triple: [Steve Prefontaine, nickname, Pre]
  • A. Pe
    Pe is a Hebrew consonant letter that represents a "p" or "f" sound and has both standard and final written forms.
  • B. P
    P is the vehicle registration code used on license plates for the Czech city of Plzeň.
  • C. Per
    Per is a Scandinavian masculine given name, commonly used in Norway, Sweden, and Denmark as a form of Peter.
  • D. PR
    PR is the two-letter postal abbreviation commonly used to refer to Puerto Rico, a Caribbean island and unincorporated territory of the United States.
  • E. PAR
    PAR is the IATA city code representing the collective airport system serving Paris, France, including major airports such as Charles de Gaulle and Orly.
  • 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: Pre
Triple: [Steve Prefontaine, nickname, Pre]
Generated description
Pre is the famous nickname of Steve Prefontaine, the iconic American middle- and long-distance runner known for his aggressive racing style and role in popularizing running in the 1970s.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Pre
Target entity description: Pre is the famous nickname of Steve Prefontaine, the iconic American middle- and long-distance runner known for his aggressive racing style and role in popularizing running in the 1970s.
  • A. Pe
    Pe is a Hebrew consonant letter that represents a "p" or "f" sound and has both standard and final written forms.
  • B. P
    P is the vehicle registration code used on license plates for the Czech city of Plzeň.
  • C. Per
    Per is a Scandinavian masculine given name, commonly used in Norway, Sweden, and Denmark as a form of Peter.
  • D. PR
    PR is the two-letter postal abbreviation commonly used to refer to Puerto Rico, a Caribbean island and unincorporated territory of the United States.
  • E. PAR
    PAR is the IATA city code representing the collective airport system serving Paris, France, including major airports such as Charles de Gaulle and Orly.
  • 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_69ad8b0e4650819090ad7cef094285e8 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcb21002c81908438170ed6f6c271 completed March 8, 2026, 7:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4db167c5881909772cf1e78717995 completed March 14, 2026, 3:50 a.m.
NEDg Description generation batch_69b4dc41a54c819099081242687e9011 completed March 14, 2026, 3:55 a.m.
NED2 Entity disambiguation (via description) batch_69b4dcb9235c8190af2b5a5d222e8413 completed March 14, 2026, 3:57 a.m.
Created at: March 8, 2026, 3:34 p.m.