Triple
T36551297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shannon Dunham |
E901263
|
entity |
| Predicate | basedOnSportInWork |
P199670
|
FINISHED |
| Object | football |
—
|
LITERAL 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: football | Statement: [Shannon Dunham, basedOnSportInWork, football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basedOnSportInWork Context triple: [Shannon Dunham, basedOnSportInWork, football]
-
A.
basedOnWorkAdaptedTo
Indicates that one work is derived from and adapted based on the content, story, or elements of another pre-existing work.
-
B.
ownsWork
Indicates that one entity has legal ownership or proprietary rights over a particular work or creation.
-
C.
basedOnCareerOf
Indicates that something (such as a work, character, or storyline) is derived from, inspired by, or modeled on the career or professional life of a particular person.
-
D.
basedOnWorkCollection
Indicates that something is derived from, adapted from, or otherwise created using a particular collection of works as its source or foundation.
-
E.
basedOnWorkPeriod
Indicates that something is determined, calculated, or defined according to a specific period of work or employment.
- F. None of above. chosen
Provenance (4 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_69f76e61217081908b79d610fe67b013 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ff4de66ba481908e7184b3cf9d4d2d |
completed | May 9, 2026, 3:08 p.m. |
| PD | Predicate disambiguation | batch_69ff4c702a5881909c6684c74807e945 |
completed | May 9, 2026, 3:02 p.m. |
| PDg | Predicate description generation | batch_69ff4de56fd48190aefdbf13c70f76ce |
completed | May 9, 2026, 3:08 p.m. |
Created at: May 3, 2026, 4:11 p.m.