Triple
T23868198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anna Karenina (2012 film score) |
E592646
|
entity |
| Predicate | hasComposerResidence |
P154252
|
FINISHED |
| Object | United Kingdom |
—
|
NE NERFINISHED |
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: United Kingdom | Statement: [Anna Karenina (2012 film score), hasComposerResidence, United Kingdom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasComposerResidence Context triple: [Anna Karenina (2012 film score), hasComposerResidence, United Kingdom]
-
A.
hasComposerInResidence
Indicates that an organization or institution has officially appointed a specific composer to serve in a resident or ongoing compositional role.
-
B.
hasPerformerResidence
Indicates that a performer is associated with a particular place as their residence.
-
C.
hasResidenceIn
Indicates that an entity lives or maintains a primary dwelling in a specified location.
-
D.
hasResidenceOn
Indicates that one entity’s place of residence is located on or along another entity, such as a street, road, or other linear feature.
-
E.
workLocationOfComposer
Indicates that a specified location is the place where a particular composer works or carries out their professional musical activities.
- 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_69e25d23a5c88190ae3999c70ca15e08 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1cae548dc8190a5f84f2cd7f9778e |
completed | April 29, 2026, 9:09 a.m. |
| PD | Predicate disambiguation | batch_69f1614a65a88190bde1efb368a151e4 |
completed | April 29, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f16e348b548190b76e50f9b611f76d |
completed | April 29, 2026, 2:34 a.m. |
Created at: April 17, 2026, 8:14 p.m.