Triple
T10541355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Natalie Goodman |
E248701
|
entity |
| Predicate | hasMother |
P1909
|
FINISHED |
| Object | Diana Goodman |
E228455
|
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: Diana Goodman | Statement: [Natalie Goodman, hasMother, Diana Goodman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Diana Goodman Context triple: [Natalie Goodman, hasMother, Diana Goodman]
-
A.
Diana Goodman
chosen
Diana Goodman is the emotionally struggling suburban mother at the center of the rock musical "Next to Normal," whose battle with mental illness drives the show's narrative.
-
B.
Diana Goodman
Diana Goodman is known as the wife of Dan Goodman.
-
C.
Diana Gordon
Diana Gordon is an American singer-songwriter and producer known for her work across R&B and pop, including co-writing major hits for artists like Beyoncé.
-
D.
Dolores Goodman
Dolores Goodman, better known professionally as Dody Goodman, was an American comedic actress and television personality recognized for her quirky, high-pitched delivery and frequent appearances on talk shows and sitcoms in the mid-20th century.
-
E.
Robyn Goodman
Robyn Goodman is an American theater producer best known for her influential work in developing and producing successful Broadway and Off-Broadway shows.
- 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_69d381c733c08190ab1dd6239f5f34ae |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d50a5918648190b16c2d1bc1bf015f |
completed | April 7, 2026, 1:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d97a10f17081909fd9465cf35685a1 |
completed | April 10, 2026, 10:30 p.m. |
Created at: April 6, 2026, 12:32 p.m.