Triple
T29561274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London Planetarium building |
E750044
|
entity |
| Predicate | formerAttractionType |
P137219
|
FINISHED |
| Object | planetarium |
—
|
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: planetarium | Statement: [London Planetarium building, formerAttractionType, planetarium]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerAttractionType Context triple: [London Planetarium building, formerAttractionType, planetarium]
-
A.
previousAttractionType
chosen
Indicates that an entity previously had a different attraction type or category before its current one.
-
B.
partOfAttractionType
Indicates that one attraction type is a component or subset of a broader, more general attraction type.
-
C.
attractionType
Indicates the specific kind or category of attraction that characterizes the relationship between entities.
-
D.
attractionTypeContext
Indicates the specific situational or contextual conditions under which an attraction between entities holds or is characterized.
-
E.
hasAttractionType
Indicates that one entity is associated with a specific kind or category of attraction (e.g., tourist, cultural, natural).
- 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_69f0bd4919e48190942b2a13d5b97d03 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69fe86cad5108190b0164b8bc6fc23ea |
completed | May 9, 2026, 12:58 a.m. |
| PD | Predicate disambiguation | batch_69fe83c0c9888190b6fc40c7f727b569 |
completed | May 9, 2026, 12:45 a.m. |
Created at: April 28, 2026, 5:20 p.m.