Triple
T7591687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hans Christian Andersen Museum |
E179748
|
entity |
| Predicate | hasBiographicalDisplays |
P6570
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Hans Christian Andersen Museum, hasBiographicalDisplays, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBiographicalDisplays Context triple: [Hans Christian Andersen Museum, hasBiographicalDisplays, yes]
-
A.
hasBiographicalTheme
Indicates that something (such as a work, text, or content) centers on or significantly involves biographical subject matter, such as a person’s life, experiences, or personal history.
-
B.
includesBiographiesOf
chosen
Indicates that one entity contains or features biographical information about another entity.
-
C.
hasPartInBiography
Indicates that a person or entity is featured or plays a role within someone’s biographical account.
-
D.
usesBiographicalStructure
Indicates that one entity employs or is organized according to the biographical structure of another entity (e.g., a work structured around a person’s life story).
-
E.
numberOfBiographies
Indicates the total count of biographies associated with a given entity.
- 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_69c69f335248819093c1006f30513708 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f9b746ac8190b255afdfb9635f72 |
completed | March 27, 2026, 9:42 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e04c2c8190a889d928515d9b8e |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:53 p.m.