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.