Triple
T14348705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goode |
E355795
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Goodey |
E355795
|
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: Goodey | Statement: [Goode, hasVariant, Goodey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Goodey Context triple: [Goode, hasVariant, Goodey]
-
A.
Goode
chosen
Goode is an English surname borne by various notable individuals across fields such as acting, politics, and academia.
-
B.
Goodes
Goodes is the surname of Adam Goodes, a prominent Australian rules footballer and Indigenous rights advocate.
-
C.
Elgood
Elgood is a small unincorporated community located in the state of West Virginia, United States.
-
D.
Gooden
Gooden is a surname most notably associated with former Major League Baseball pitcher Dwight "Doc" Gooden, a dominant star of the 1980s New York Mets.
-
E.
Gurney
Gurney is an English surname historically associated with several notable families, including Quaker bankers, philanthropists, and public figures.
- 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_69d82790a7e08190877e2d349b2e8d8e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8e8d081c8190ac805726a3e98f4c |
completed | April 14, 2026, 6:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd46a12ad08190a2f0dc5890ed5ce9 |
completed | May 8, 2026, 2:12 a.m. |
Created at: April 10, 2026, 1:14 a.m.