Triple
T10686678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Davis |
E251894
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Joy |
E136603
|
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: Joy | Statement: [John Davis, notableWork, Joy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joy Context triple: [John Davis, notableWork, Joy]
-
A.
Joy
chosen
"Joy" is a 2015 biographical comedy-drama film starring Jennifer Lawrence as a struggling single mother who becomes a successful inventor and entrepreneur.
-
B.
Joy
Joy is the surname of Bill Joy, the influential American computer scientist and co-founder of Sun Microsystems.
-
C.
Joy
Joy is a given name used for people of any gender, derived from the English word expressing happiness and delight.
-
D.
Joy
Joy is the personified emotion of happiness and optimism in Pixar's animated film "Inside Out," guiding the young girl Riley through her childhood experiences.
-
E.
Joy
"Joy" is a film featuring Isabella Rossellini, known for her role in this character-driven drama.
- 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_69d6aa5bd7c08190a816e733b4045c23 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fd192220819088eff88148376266 |
completed | April 9, 2026, 1:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d98894cea48190877a015dcb645bee |
completed | April 10, 2026, 11:32 p.m. |
Created at: April 8, 2026, 9:10 p.m.