Triple
T15506839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lisa Office System |
E379103
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object | LisaProject |
E77077
|
NE FINISHED |
How this triple was built (2 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: LisaProject | Statement: [Lisa Office System, hasComponent, LisaProject]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LisaProject Context triple: [Lisa Office System, hasComponent, LisaProject]
-
A.
LisaProject
chosen
LisaProject was a project management and scheduling application included with Apple's Lisa computer system, designed to help users plan and track tasks and timelines.
-
B.
Lisa
Lisa is the central protagonist of the French romantic drama film "L'Appartement," around whom the story’s mystery and emotional tension revolve.
-
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 the central protagonist of the film "Wicker Park," around whom the story’s romantic mystery and emotional tension revolve.
-
E.
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.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03fcea8888190a7b69aca360183c3 |
completed | April 16, 2026, 1:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff366e472c819093472da2a49593c6 |
completed | May 9, 2026, 1:28 p.m. |
Created at: April 10, 2026, 3:55 a.m.