Triple
T3262707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Ortiz |
E68448
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Rake |
E255991
|
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: Rake | Statement: [John Ortiz, notableWork, Rake]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rake Context triple: [John Ortiz, notableWork, Rake]
-
A.
Rake
Rake is a Ruby-based build automation tool similar to Make, used to define and run tasks via Ruby code.
-
B.
Rake
chosen
Rake is an Australian television legal comedy-drama series centered on a brilliant but self-destructive criminal defense barrister.
-
C.
Rags
Rags is a lesser-known Broadway musical by composer Stephen Schwartz that explores the struggles and hopes of Jewish immigrants in early 20th-century America.
-
D.
Dame
Dame is a British honorific title bestowed primarily upon women in recognition of significant contributions to national life, often in the arts, public service, or other distinguished fields.
-
E.
Dame
Dame is the popular nickname of NBA All-Star point guard Damian Lillard, known for his clutch shooting and leadership.
- 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_69ad8590444081909e8107a8aeef3a23 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adafa908e881908cbb2ad137819ffb |
completed | March 8, 2026, 5:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b28ee2ec8481908a0c0f4a32c97fe0 |
completed | March 12, 2026, 10:01 a.m. |
Created at: March 8, 2026, 3:09 p.m.