Triple

T11987942
Position Surface form Disambiguated ID Type / Status
Subject Stuart A. Roosa E285329 entity
Predicate hasNickname P39 FINISHED
Object Stu
Stu is the nickname of Stuart A. Roosa, the American astronaut who served as Command Module Pilot on the Apollo 14 mission to the Moon.
E958440 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: Stu | Statement: [Stuart A. Roosa, hasNickname, Stu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stu
Context triple: [Stuart A. Roosa, hasNickname, Stu]
  • A. STU
    STU is a major public technical university in Bratislava, Slovakia, known for its engineering, technology, and applied science programs.
  • B. Stuvsta
    Stuvsta is a residential district and commuter suburb in the southern Stockholm area of Sweden, known for its villas, local center, and good rail connections to central Stockholm.
  • C. Stan
    Stan is a fast-talking, over-the-top used-boat and later used-coffin salesman known for his loud jacket and relentless sales pitches in the Monkey Island adventure game series.
  • D. Stan
    "Stan" is a critically acclaimed song by Eminem that tells the dark, narrative-driven story of an obsessive fan through a series of letters.
  • E. Stan
    Stan is a probabilistic programming language and platform widely used for Bayesian statistical modeling and inference, particularly via methods like Hamiltonian Monte Carlo.
  • 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: Stu
Triple: [Stuart A. Roosa, hasNickname, Stu]
Generated description
Stu is the nickname of Stuart A. Roosa, the American astronaut who served as Command Module Pilot on the Apollo 14 mission to the Moon.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Stu
Target entity description: Stu is the nickname of Stuart A. Roosa, the American astronaut who served as Command Module Pilot on the Apollo 14 mission to the Moon.
  • A. STU
    STU is a major public technical university in Bratislava, Slovakia, known for its engineering, technology, and applied science programs.
  • B. Stuvsta
    Stuvsta is a residential district and commuter suburb in the southern Stockholm area of Sweden, known for its villas, local center, and good rail connections to central Stockholm.
  • C. Stan
    Stan is a fast-talking, over-the-top used-boat and later used-coffin salesman known for his loud jacket and relentless sales pitches in the Monkey Island adventure game series.
  • D. Stan
    Stan is an Australian subscription video-on-demand streaming service offering films, TV series, and original content.
  • E. Stan
    "Stan" is a critically acclaimed song by Eminem that tells the dark, narrative-driven story of an obsessive fan through a series of letters.
  • 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_69d6ab44a77c8190a652f4b27164e4ef completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903ae28708190a826bad1624343eb completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f472492ebc8190b064e691bb70e356 completed May 1, 2026, 9:28 a.m.
NEDg Description generation batch_69f47b7c5af08190ab0bff1232530a0c completed May 1, 2026, 10:07 a.m.
NED2 Entity disambiguation (via description) batch_69f47dd51e648190bddd41766221e22d completed May 1, 2026, 10:17 a.m.
Created at: April 8, 2026, 9:46 p.m.