Triple
T1476611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lawrence Weingarten |
E30855
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Pat and Mike
Pat and Mike is a 1952 sports comedy film starring Katharine Hepburn and Spencer Tracy, known for its witty script and depiction of a female athlete challenging gender norms.
|
E169573
|
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: Pat and Mike | Statement: [Lawrence Weingarten, notableWork, Pat and Mike]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pat and Mike Context triple: [Lawrence Weingarten, notableWork, Pat and Mike]
-
A.
Pete
Pete is the nickname of Grover Cleveland Alexander, a Hall of Fame Major League Baseball pitcher and one of the greatest hurlers of the early 20th century.
-
B.
Pete
Pete is a common masculine given name, typically used as a familiar or informal form of the name Peter.
-
C.
MIKE
MIKE is a high-resolution optical spectrograph used on the Magellan Telescopes for detailed astronomical spectroscopy.
-
D.
Mick
Mick is the commonly used nickname of American politician and former White House Chief of Staff Mick Mulvaney.
-
E.
Micheal
Micheal is a given name, typically a variant spelling of the more common name Michael.
- 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: Pat and Mike Triple: [Lawrence Weingarten, notableWork, Pat and Mike]
Generated description
Pat and Mike is a 1952 sports comedy film starring Katharine Hepburn and Spencer Tracy, known for its witty script and depiction of a female athlete challenging gender norms.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pat and Mike Target entity description: Pat and Mike is a 1952 sports comedy film starring Katharine Hepburn and Spencer Tracy, known for its witty script and depiction of a female athlete challenging gender norms.
-
A.
Pete
Pete is the nickname of Grover Cleveland Alexander, a Hall of Fame Major League Baseball pitcher and one of the greatest hurlers of the early 20th century.
-
B.
Pete
Pete is a common masculine given name, typically used as a familiar or informal form of the name Peter.
-
C.
MIKE
MIKE is a high-resolution optical spectrograph used on the Magellan Telescopes for detailed astronomical spectroscopy.
-
D.
Mick
Mick is the commonly used nickname of American politician and former White House Chief of Staff Mick Mulvaney.
-
E.
Micheal
Micheal is a given name, typically a variant spelling of the more common name Michael.
- 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_69a498fe55a88190ab7f9e40ace88e49 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c603f9e88190b340734709534860 |
completed | March 1, 2026, 11:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad15add78c8190843efd75bbe8423f |
completed | March 8, 2026, 6:22 a.m. |
| NEDg | Description generation | batch_69ad184626f48190a15ee8bb4f9f6f7c |
completed | March 8, 2026, 6:33 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad18dca6b48190a63b67a7823611c8 |
completed | March 8, 2026, 6:36 a.m. |
Created at: March 1, 2026, 8:11 p.m.