Triple
T6953861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Star Trek novels |
E161191
|
entity |
| Predicate | hasContributor |
P4244
|
FINISHED |
| Object |
David Mack
David Mack is an American author best known for his numerous Star Trek tie-in novels and related science fiction works.
|
E632069
|
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: David Mack | Statement: [Star Trek novels, hasContributor, David Mack]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: David Mack Context triple: [Star Trek novels, hasContributor, David Mack]
-
A.
Alan Ford
Alan Ford is a British character actor best known for his tough-guy and gangster roles in films by director Guy Ritchie.
-
B.
Nick Meyer
Nick Meyer is a film executive and producer known for his work on major studio projects, including the fantasy adventure film "Dungeons & Dragons: Honor Among Thieves."
-
C.
Paul Darrow
Paul Darrow was the son of famed American lawyer Clarence Darrow and a businessman who managed many of his father's financial affairs.
-
D.
Brian MacDevitt
Brian MacDevitt is a Tony Award–winning American lighting designer renowned for his work on numerous high-profile Broadway productions.
-
E.
Charles Gunn
Charles Gunn is a street-smart vampire hunter who becomes a key ally and member of Angel Investigations in the television series "Angel."
- 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: David Mack Triple: [Star Trek novels, hasContributor, David Mack]
Generated description
David Mack is an American author best known for his numerous Star Trek tie-in novels and related science fiction works.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: David Mack Target entity description: David Mack is an American author best known for his numerous Star Trek tie-in novels and related science fiction works.
-
A.
Alan Ford
Alan Ford is a British character actor best known for his tough-guy and gangster roles in films by director Guy Ritchie.
-
B.
Nick Meyer
Nick Meyer is a film executive and producer known for his work on major studio projects, including the fantasy adventure film "Dungeons & Dragons: Honor Among Thieves."
-
C.
Paul Darrow
Paul Darrow was the son of famed American lawyer Clarence Darrow and a businessman who managed many of his father's financial affairs.
-
D.
Brian MacDevitt
Brian MacDevitt is a Tony Award–winning American lighting designer renowned for his work on numerous high-profile Broadway productions.
-
E.
Charles Gunn
Charles Gunn is a street-smart vampire hunter who becomes a key ally and member of Angel Investigations in the television series "Angel."
- 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_69c68852a9a0819097797e31d492e273 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dacca12481908942ba793a104cc3 |
completed | March 27, 2026, 7:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7587ee1b08190b9f53ab7df4a4a58 |
completed | March 28, 2026, 4:26 a.m. |
| NEDg | Description generation | batch_69c75a8998308190b99a11d5aaf7436b |
completed | March 28, 2026, 4:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c75afddbf88190884d98e4b8a0c9eb |
completed | March 28, 2026, 4:37 a.m. |
Created at: March 27, 2026, 2:29 p.m.