Triple
T15996591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rande Gerber |
E387982
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Gerber |
E782505
|
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: Gerber | Statement: [Rande Gerber, familyName, Gerber]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gerber Context triple: [Rande Gerber, familyName, Gerber]
-
A.
Gerber
Gerber is a small unincorporated rural community located in Tehama County in Northern California.
-
B.
Gerber
chosen
Gerber is a surname most commonly associated with individuals of German or Swiss origin, including various notable figures in entertainment, business, and sports.
-
C.
Gerber Products Company
Gerber Products Company is a leading American baby food and infant nutrition brand known for its wide range of purees, cereals, and snacks for young children.
-
D.
Playtex
Playtex is a well-known American brand specializing in bras, shapewear, and other intimate apparel products.
-
E.
Baby-O
Baby-O is a film directed by Charles Matthau, known as one of his notable works in American cinema.
- 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_69d86daa562c81908aacc179c0fe8fb5 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e157882ef0819081143e530bd6413c |
completed | April 16, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffc3d79dec8190b02e003f93e5dad6 |
completed | May 9, 2026, 11:31 p.m. |
Created at: April 10, 2026, 4:55 a.m.