Triple
T1617633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | STS-61 |
E34755
|
entity |
| Predicate | crewMember |
P2094
|
FINISHED |
| Object |
Tom Akers
Tom Akers is a former NASA astronaut and U.S. Air Force officer best known for his multiple Space Shuttle missions, including servicing the Hubble Space Telescope.
|
E203631
|
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: Tom Akers | Statement: [STS-61, crewMember, Tom Akers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Akers Context triple: [STS-61, crewMember, Tom Akers]
-
A.
Tom Leppert
Tom Leppert is an American businessman and politician who served as the mayor of Dallas, Texas, and later ran for the U.S. Senate.
-
B.
Jeffrey Fuller
Jeffrey Fuller is known primarily as the son of prominent American lawyer, feminist, and civil liberties advocate Crystal Eastman.
-
C.
Tom Luddy
Tom Luddy was an American film producer, curator, and influential cinephile best known as a co-founder and long-time guiding force of the Telluride Film Festival.
-
D.
David Scearce
David Scearce is a Canadian screenwriter best known for adapting Christopher Isherwood’s novel into the acclaimed film "A Single Man."
-
E.
Ted Cheesman
Ted Cheesman was a film editor best known for his work on classic Hollywood productions, including the 1933 monster film "King Kong."
- 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: Tom Akers Triple: [STS-61, crewMember, Tom Akers]
Generated description
Tom Akers is a former NASA astronaut and U.S. Air Force officer best known for his multiple Space Shuttle missions, including servicing the Hubble Space Telescope.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tom Akers Target entity description: Tom Akers is a former NASA astronaut and U.S. Air Force officer best known for his multiple Space Shuttle missions, including servicing the Hubble Space Telescope.
-
A.
Tom Leppert
Tom Leppert is an American businessman and politician who served as the mayor of Dallas, Texas, and later ran for the U.S. Senate.
-
B.
Jeffrey Fuller
Jeffrey Fuller is known primarily as the son of prominent American lawyer, feminist, and civil liberties advocate Crystal Eastman.
-
C.
Tom Luddy
Tom Luddy was an American film producer, curator, and influential cinephile best known as a co-founder and long-time guiding force of the Telluride Film Festival.
-
D.
David Scearce
David Scearce is a Canadian screenwriter best known for adapting Christopher Isherwood’s novel into the acclaimed film "A Single Man."
-
E.
Ted Cheesman
Ted Cheesman was a film editor best known for his work on classic Hollywood productions, including the 1933 monster film "King Kong."
- 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_69a885ffc5ec819091afa325d5f9611c |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a909addb348190a80a97422efcaa63 |
completed | March 5, 2026, 4:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adbf3ffc4081909197690046d8ff22 |
completed | March 8, 2026, 6:26 p.m. |
| NEDg | Description generation | batch_69adc0a3fdd88190b0ffa98db1b5cf80 |
completed | March 8, 2026, 6:32 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adc12c894881909c9a82fc9e363a41 |
completed | March 8, 2026, 6:34 p.m. |
Created at: March 4, 2026, 7:28 p.m.