Triple
T394482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bradbury Science Museum |
E8951
|
entity |
| Predicate | charges |
P6310
|
FINISHED |
| Object | free admission |
—
|
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: free admission | Statement: [Bradbury Science Museum, charges, free admission]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: charges Context triple: [Bradbury Science Museum, charges, free admission]
-
A.
charge
Indicates that one entity formally accuses another of an offense or imposes a financial cost or obligation on them.
-
B.
chargeOftenUsed
Indicates that an entity is frequently subjected to or associated with a particular charge (such as a legal, financial, or electrical charge).
-
C.
legalCharge
Indicates that an authority has formally accused an entity of committing a specific legal offense or violation.
-
D.
hasCharge
Indicates that an entity possesses a specific electrical or formal charge, such as positive, negative, or neutral.
-
E.
featuresCharge
chosen
Indicates that one entity includes, offers, or is characterized by a particular charge (such as a fee, cost, or pricing component).
- 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_69a2e7f55c60819097aff65ea2ca2832 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec77a8a08190b6f96373aa8c1346 |
completed | Feb. 28, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69a2e96bd3848190a66ca14dfbd26da5 |
completed | Feb. 28, 2026, 1:11 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.