Triple
T18077769
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | STS-132 |
E432601
|
entity |
| Predicate | crewMember |
P2094
|
FINISHED |
| Object | Michael T. Good |
—
|
NE NERFINISHED |
How this triple was built (2 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: Michael T. Good | Statement: [STS-132, crewMember, Michael T. Good]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael T. Good Context triple: [STS-132, crewMember, Michael T. Good]
-
A.
Michael T. Good
chosen
Michael T. Good is a NASA astronaut and retired U.S. Air Force colonel who flew on multiple Space Shuttle missions, including the final servicing mission to the Hubble Space Telescope.
-
B.
Dan Goodman
Dan Goodman is a central character in the rock musical "Next to Normal," portrayed as a devoted husband and father struggling to hold his family together amid his wife's severe mental illness.
-
C.
Gary K. Wolfe
Gary K. Wolfe is an American literary critic and scholar best known for his influential work on science fiction and fantasy literature.
-
D.
Mark J. Feist
Mark J. Feist is a music producer and songwriter known for his work with prominent pop and R&B artists.
-
E.
John C. Wright
John C. Wright is an American science fiction and fantasy author known for his intricate world-building, philosophical themes, and works such as the "Golden Age" trilogy.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9070cac81909fa9473fb1c3f1c7 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4d9f6a85481909894c39c8be98d5d |
completed | April 19, 2026, 1:34 p.m. |
Created at: April 10, 2026, 10:26 a.m.