Triple
T31394249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ida Ilsted |
E800820
|
entity |
| Predicate | workLocationAsModel |
P98374
|
FINISHED |
| Object | Hammershøi's apartments in Copenhagen |
—
|
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: Hammershøi's apartments in Copenhagen | Statement: [Ida Ilsted, workLocationAsModel, Hammershøi's apartments in Copenhagen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workLocationAsModel Context triple: [Ida Ilsted, workLocationAsModel, Hammershøi's apartments in Copenhagen]
-
A.
locationInWork
Indicates that one entity specifies the place or setting where another entity occurs, is situated, or takes place within a particular work (e.g., a scene’s location in a film or a chapter’s setting in a book).
-
B.
locationOfWork
Indicates the place or site where an entity performs its work or carries out its professional activities.
-
C.
workModel
Indicates that one entity serves as, or is based on, a particular model used for work, operation, or functional behavior.
-
D.
modelingLocation
chosen
Indicates the place or setting where the modeling activity or process occurs.
-
E.
depictsWorkLocation
Indicates that one entity visually represents the place where another entity performs its work or professional activities.
- F. None of above.
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_69f224ea9998819086ae2e4f4f4091c8 |
completed | April 29, 2026, 3:34 p.m. |
| NER | Named-entity recognition | batch_69f6a5f71b2c8190aade8a83f465be0c |
completed | May 3, 2026, 1:33 a.m. |
| PD | Predicate disambiguation | batch_69f69fe66df08190958558d63ee623d9 |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 29, 2026, 9:19 p.m.