Triple
T13384604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hap and Leonard |
E319406
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Hap Collins
Hap Collins is a working-class, wisecracking East Texan and reluctant adventurer who stars as one half of the crime-fighting duo in Joe R. Lansdale’s "Hap and Leonard" series.
|
E1036413
|
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: Hap Collins | Statement: [Hap and Leonard, mainCharacter, Hap Collins]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hap Collins Context triple: [Hap and Leonard, mainCharacter, Hap Collins]
-
A.
Al Collins
Al Collins is a songwriter best known for co-writing the rock and roll standard "Slippin' and Slidin'."
-
B.
Wayne Collins
Wayne Collins is a fictional character from the film "The Gift," involved in the movie’s tense, psychological storyline.
-
C.
Andy Collins
Andy Collins is a cinematographer best known for his work on the British film "Brassed Off."
-
D.
Steve Collins
Steve Collins is a fictional character appearing in the classic 1941 screwball comedy film "The Bride Came C.O.D."
-
E.
Dennis Collins
Dennis Collins is an American entrepreneur and classic car expert best known for his extensive work in automotive restoration and appearances on car-related television programs.
- 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: Hap Collins Triple: [Hap and Leonard, mainCharacter, Hap Collins]
Generated description
Hap Collins is a working-class, wisecracking East Texan and reluctant adventurer who stars as one half of the crime-fighting duo in Joe R. Lansdale’s "Hap and Leonard" series.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hap Collins Target entity description: Hap Collins is a working-class, wisecracking East Texan and reluctant adventurer who stars as one half of the crime-fighting duo in Joe R. Lansdale’s "Hap and Leonard" series.
-
A.
Al Collins
Al Collins is a songwriter best known for co-writing the rock and roll standard "Slippin' and Slidin'."
-
B.
Wayne Collins
Wayne Collins is a fictional character from the film "The Gift," involved in the movie’s tense, psychological storyline.
-
C.
Andy Collins
Andy Collins is a cinematographer best known for his work on the British film "Brassed Off."
-
D.
Steve Collins
Steve Collins is a fictional character appearing in the classic 1941 screwball comedy film "The Bride Came C.O.D."
-
E.
Dennis Collins
Dennis Collins is an American entrepreneur and classic car expert best known for his extensive work in automotive restoration and appearances on car-related television programs.
- 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_69d806b886bc8190b676e7768b8e01c5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dadce80158819082156eaeaeda3bd8 |
completed | April 11, 2026, 11:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7268cf04c8190a35fd48ce81c149e |
completed | May 3, 2026, 10:42 a.m. |
| NEDg | Description generation | batch_69f7276776ec81908769cd9f1cc4707e |
completed | May 3, 2026, 10:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7280cbb6c819090bee7862e00b900 |
completed | May 3, 2026, 10:48 a.m. |
Created at: April 9, 2026, 9:33 p.m.