Triple
T20174848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neon Museum |
E492062
|
entity |
| Predicate | typeOfTouristAttraction |
P8077
|
FINISHED |
| Object | specialty museum |
—
|
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: specialty museum | Statement: [Neon Museum, typeOfTouristAttraction, specialty museum]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfTouristAttraction Context triple: [Neon Museum, typeOfTouristAttraction, specialty museum]
-
A.
attractionType
chosen
Indicates the specific kind or category of attraction that characterizes the relationship between entities.
-
B.
typeOfLandmark
Indicates the specific category or kind of landmark that an entity belongs to (e.g., monument, natural feature, building).
-
C.
hasTouristAttractionRole
Indicates that an entity serves in the capacity or function of a tourist attraction for another entity (such as a place, organization, or area).
-
D.
isMajorAttractionFor
Indicates that something serves as a primary or highly significant draw or point of interest for a particular audience, group, or location.
-
E.
tourismType
Indicates the specific category or kind of tourism activity or experience associated with an 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_69da6266c6888190bc1a3ecf24814d34 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e668eaa3b88190bef4f2db0125fdfc |
completed | April 20, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69e55b0c11cc8190836d1eee5945f000 |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:36 p.m.