Triple
T9833363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jaime Lerner |
E239040
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Lerner |
E181685
|
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: Lerner | Statement: [Jaime Lerner, familyName, Lerner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lerner Context triple: [Jaime Lerner, familyName, Lerner]
-
A.
Lerner
chosen
Lerner is a surname most notably associated with Sandy Lerner, the co-founder of Cisco Systems and a prominent philanthropist and businesswoman.
-
B.
Lerman
Lerman is a surname most notably associated with American actor Logan Lerman, known for roles in films such as the "Percy Jackson" series and "The Perks of Being a Wallflower."
-
C.
Ted Lerner
Ted Lerner was an American real estate developer and principal owner of the Washington Nationals Major League Baseball team.
-
D.
Samuel Lerner
Samuel Lerner was a 20th-century songwriter and lyricist best known for composing music and lyrics for early film and radio, including the theme song for the cartoon character Betty Boop.
-
E.
Julian Lerner
Julian Lerner is an American child actor known for his roles in family-oriented films and television series.
- 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_69ca84e314108190978324a4bdb959f8 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb336bfc4819084f0d4d6d1867484 |
completed | April 2, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1d5c448388190818e4cc5e3a42dfc |
completed | April 5, 2026, 3:23 a.m. |
Created at: March 30, 2026, 8:32 p.m.