Triple
T3802861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Goodman |
E91731
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Goodman |
E339208
|
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: Goodman | Statement: [John Goodman, familyName, Goodman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Goodman Context triple: [John Goodman, familyName, Goodman]
-
A.
Goodman
chosen
Goodman is a common English-language surname borne by numerous notable individuals across fields such as philosophy, arts, and entertainment.
-
B.
Sherwin
Sherwin is a surname most notably associated with Martin J. Sherwin, an American historian known for his work on nuclear history and the life of J. Robert Oppenheimer.
-
C.
Wyman-Gordon
Wyman-Gordon is an industrial manufacturer known for producing high-strength forged components, particularly for the aerospace and energy industries.
-
D.
Sullivan & Son
Sullivan & Son is an American sitcom that follows a corporate lawyer who leaves his big-city career to run his family's bar in a working-class Pittsburgh neighborhood.
-
E.
Otis
Otis is a globally recognized manufacturer of elevators, escalators, and moving walkways, known for pioneering vertical transportation technologies.
- 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_69aed96354f48190a768966d6bd19b04 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee7bacf2881908198a77063d15d16 |
completed | March 9, 2026, 3:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4f06889c88190ab4d8da7f0dfeadd |
completed | March 14, 2026, 5:21 a.m. |
Created at: March 9, 2026, 3:15 p.m.