Triple
T11134743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Commodore Amiga 1200 |
E263380
|
entity |
| Predicate | graphicsChip |
P20530
|
FINISHED |
| Object |
Lisa
Lisa is the advanced AGA graphics chipset used in the Commodore Amiga 1200 computer, providing enhanced color and display capabilities over earlier Amiga systems.
|
E907936
|
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: Lisa | Statement: [Commodore Amiga 1200, graphicsChip, Lisa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lisa Context triple: [Commodore Amiga 1200, graphicsChip, Lisa]
-
A.
Lisa
Lisa is a central character in the science fiction adventure film "Zathura: A Space Adventure," where she becomes unwittingly involved in her younger brothers' perilous journey through outer space.
-
B.
Lisa
Lisa is the given name of Australian musician and composer Lisa Gerrard, renowned for her work as part of Dead Can Dance and for her film scores.
-
C.
Lisa
Lisa is the central protagonist of the film "Wicker Park," around whom the story’s romantic mystery and emotional tension revolve.
-
D.
Lisa
Lisa is a person known primarily for holding a position or role that was later taken over by Denise.
-
E.
Lisa
Lisa is a close friend and confidante of Sophie Sheridan in the Mamma Mia! universe.
- 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: Lisa Triple: [Commodore Amiga 1200, graphicsChip, Lisa]
Generated description
Lisa is the advanced AGA graphics chipset used in the Commodore Amiga 1200 computer, providing enhanced color and display capabilities over earlier Amiga systems.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lisa Target entity description: Lisa is the advanced AGA graphics chipset used in the Commodore Amiga 1200 computer, providing enhanced color and display capabilities over earlier Amiga systems.
-
A.
Lisa
Lisa is a custom-designed integrated circuit that served as a key support chipset component in early Apple Macintosh computers, handling functions such as memory and system control.
-
B.
Lisa
Lisa is a person known primarily for holding a position or role that was later taken over by Denise.
-
C.
Lisa
Lisa is the given name of Australian musician and composer Lisa Gerrard, renowned for her work as part of Dead Can Dance and for her film scores.
-
D.
Lisa
Lisa is a fictional character from the psychological horror film "The Voices," known for her involvement with the disturbed protagonist and the film’s darkly comedic, violent events.
-
E.
Lisa
Lisa is a feminine given name commonly used in English-speaking countries, often as a shortened form of Elizabeth or Melissa.
- 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_69d6aa9c0ba08190bbd19c217489b755 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e85daddc8190a1ae2a4a75cc8d50 |
completed | April 9, 2026, 5:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e441fa286881909a8279a8ea6944e7 |
completed | April 19, 2026, 2:46 a.m. |
| NEDg | Description generation | batch_69e44c09163481909d6a469b1e50b6ff |
completed | April 19, 2026, 3:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e4519f4d408190be9863c72006ecad |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 8, 2026, 9:28 p.m.