Triple
T9105533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Rhinebeck Aerodrome |
E218467
|
entity |
| Predicate | hasMuseumComponent |
P87179
|
FINISHED |
| Object | static exhibits |
—
|
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: static exhibits | Statement: [Old Rhinebeck Aerodrome, hasMuseumComponent, static exhibits]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMuseumComponent Context triple: [Old Rhinebeck Aerodrome, hasMuseumComponent, static exhibits]
-
A.
hasMuseumFunction
Indicates that an entity serves the role or performs the function of a museum.
-
B.
hasMuseumType
Indicates that an entity is classified as a museum of a specific type or category.
-
C.
hasMuseumAt
Indicates that a museum is located at or exists in a specified place or location.
-
D.
hasMuseumTheme
Indicates that something (such as a museum, exhibit, or collection) is characterized by or dedicated to a particular thematic focus.
-
E.
hasMuseumOrTreasureHouse
Indicates that an entity contains, hosts, or is associated with a museum or treasure house.
- 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_69ca83db7448819090d0a5de842ef2ac |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca5714d048190a633caaaa707ac3b |
completed | April 1, 2026, 4:56 a.m. |
| PD | Predicate disambiguation | batch_69cc65fc7f408190a5846e29ab3b97e5 |
completed | April 1, 2026, 12:25 a.m. |
| PDg | Predicate description generation | batch_69cc6a3c78388190a7436acc0e44ff55 |
completed | April 1, 2026, 12:43 a.m. |
Created at: March 30, 2026, 7:16 p.m.