Triple
T17305849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martin Lawrence |
E420162
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Martin
Martin is a 1990s American sitcom starring comedian Martin Lawrence as a wisecracking Detroit radio host navigating relationships, work, and everyday life.
|
E1014832
|
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: Martin | Statement: [Martin Lawrence, notableWork, Martin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Martin Context triple: [Martin Lawrence, notableWork, Martin]
-
A.
Martin
Martin is the middle name of Henry Martin Tupper, an individual likely known in historical or biographical records.
-
B.
Martin
Martin is the given name of Klaus Martin Einstein, the son of physicist Hans Albert Einstein and grandson of Albert Einstein.
-
C.
Martin
Martin is a central character in the Australian television drama series "The Newsreader," which follows the turbulent personal and professional lives of 1980s newsroom staff.
-
D.
Martin
Martin is the middle name of Roswell Field, an American lawyer best known for his involvement in the Dred Scott case.
-
E.
Martin
Martin is a masculine given name of Latin origin, commonly used in many European languages.
- 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: Martin Triple: [Martin Lawrence, notableWork, Martin]
Generated description
Martin is a 1990s American sitcom starring comedian Martin Lawrence as a wisecracking Detroit radio host navigating relationships, work, and everyday life.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Martin Target entity description: Martin is a 1990s American sitcom starring comedian Martin Lawrence as a wisecracking Detroit radio host navigating relationships, work, and everyday life.
-
A.
Martin
chosen
Martin is a 1990s American sitcom starring Martin Lawrence as a wisecracking Detroit radio DJ and later TV personality, known for its energetic humor and memorable supporting characters.
-
B.
Martin
Martin is a fictional character from the television comedy series "Blunt Talk."
-
C.
Martin
Martin is a key supporting character in the British comedy-drama series "Fleabag," known for his abrasive personality, inappropriate behavior, and tense relationship with the show's protagonist and her family.
-
D.
Martin
Martin is a central character in the Australian television drama series "The Newsreader," which follows the turbulent personal and professional lives of 1980s newsroom staff.
-
E.
Martin
Martin is a fictional character from the dark comedy film "Mini's First Time," involved in the movie’s twisted family and blackmail plot.
- F. None of above.
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_69d889d22b848190a4663d0b8f8f76e7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e438ff3ee08190ab4c44a22f86b38b |
completed | April 19, 2026, 2:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a018c440c58819084792fcd6b7a7a79 |
completed | May 11, 2026, 7:59 a.m. |
| NEDg | Description generation | batch_6a018d9651a48190b8a465741bb5b549 |
completed | May 11, 2026, 8:04 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a018eb4aed881908bf0f6837f373d04 |
completed | May 11, 2026, 8:09 a.m. |
Created at: April 10, 2026, 5:43 a.m.