Triple
T2232445
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Car Wash |
E49199
|
entity |
| Predicate | title |
P38
|
FINISHED |
| Object | Car Wash |
E49199
|
NE 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: Car Wash | Statement: [Car Wash, title, Car Wash]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Car Wash Context triple: [Car Wash, title, Car Wash]
-
A.
Car Wash
chosen
Car Wash is a 1976 comedy film set in a Los Angeles car wash, known for its ensemble cast, funky soundtrack, and satirical look at working-class life.
-
B.
Wash.
Wash. is the standard legal citation abbreviation used to refer to decisions of the Washington Supreme Court.
-
C.
Orange Garage
Orange Garage is a multi-level parking facility serving visitors to the Disney Springs shopping, dining, and entertainment district at Walt Disney World Resort in Florida.
-
D.
Laundry Service
"Laundry Service" is the breakthrough 2001 studio album by Colombian singer Shakira that marked her successful crossover into the English-language pop market.
-
E.
Ventra
Ventra is the contactless fare payment system used across Chicago’s public transit network, including buses and trains.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a88aa84bdc819086df50e9c20b301e |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc06d26bc8190a85ddb6312d2df08 |
completed | March 7, 2026, 6:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae6b001ee481909b28aea25ad7b906 |
completed | March 9, 2026, 6:38 a.m. |
Created at: March 4, 2026, 7:47 p.m.