Triple
T3396205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgia Avenue–Petworth station |
E71533
|
entity |
| Predicate | ticketingCurrency |
P245
|
FINISHED |
| Object | U.S. dollars |
—
|
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: U.S. dollars | Statement: [Georgia Avenue–Petworth station, ticketingCurrency, U.S. dollars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ticketingCurrency Context triple: [Georgia Avenue–Petworth station, ticketingCurrency, U.S. dollars]
-
A.
prizeMoneyCurrency
Indicates the currency in which the prize money is denominated or paid.
-
B.
franchiseBasePriceCurrency
Indicates the currency in which the base price of a franchise is denominated.
-
C.
currency
chosen
Indicates that one entity serves as the medium of exchange or monetary unit used by another entity (such as a country, region, or system).
-
D.
currencyType
Indicates the specific kind of monetary unit or currency associated with an entity or transaction.
-
E.
currencyDepicted
Indicates that one entity visually represents or shows the image or symbol of a particular currency on it.
- 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_69ad85a9c4a88190a854019341cb3b60 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb856158c81908dd7d3f1f8d6af74 |
completed | March 8, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69adadf705608190975423779430cc58 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:14 p.m.