Triple
T21699627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LA Waterfront Red Car |
E535619
|
entity |
| Predicate | hasVehicle |
P7735
|
FINISHED |
| Object |
Car 501
Car 501 is a historic LA Waterfront Red Car trolley vehicle that operated as part of the heritage streetcar service along the Los Angeles waterfront.
|
E1496975
|
NE FINISHED |
How this triple was built (4 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 501 | Statement: [LA Waterfront Red Car, hasVehicle, Car 501]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Car 501 Context triple: [LA Waterfront Red Car, hasVehicle, Car 501]
-
A.
Car 99
Car 99 is a 1935 American crime drama film starring Fred MacMurray as a member of a state highway patrol.
-
B.
The Car
The Car is a 1977 American horror film about a mysterious, driverless automobile that terrorizes a small desert town.
-
C.
The Car
"The Car" is a 2022 studio album by English rock band Arctic Monkeys, noted for its lush orchestration, cinematic atmosphere, and introspective songwriting.
-
D.
Can Car
Can Car is the common abbreviation for Canadian Car and Foundry, a historic Canadian manufacturer best known for producing railway rolling stock, aircraft, and other transportation equipment.
-
E.
Car-Car
Car-Car is a musical piece or segment featured within the larger work "In Concert."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Car 501 Triple: [LA Waterfront Red Car, hasVehicle, Car 501]
Generated description
Car 501 is a historic LA Waterfront Red Car trolley vehicle that operated as part of the heritage streetcar service along the Los Angeles waterfront.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Car 501 Target entity description: Car 501 is a historic LA Waterfront Red Car trolley vehicle that operated as part of the heritage streetcar service along the Los Angeles waterfront.
-
A.
Car 99
Car 99 is a 1935 American crime drama film starring Fred MacMurray as a member of a state highway patrol.
-
B.
The Car
"The Car" is a 2022 studio album by English rock band Arctic Monkeys, noted for its lush orchestration, cinematic atmosphere, and introspective songwriting.
-
C.
The Car
The Car is a 1977 American horror film about a mysterious, driverless automobile that terrorizes a small desert town.
-
D.
Can Car
Can Car is the common abbreviation for Canadian Car and Foundry, a historic Canadian manufacturer best known for producing railway rolling stock, aircraft, and other transportation equipment.
-
E.
Car-Car
Car-Car is a musical piece or segment featured within the larger work "In Concert."
- F. None of above. chosen
Provenance (5 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_69e0c46a6ee481908836e1420fb78c9b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef9b7de9888190bbca7717a32f9888 |
completed | April 27, 2026, 5:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a1e2755708190afd098c5c673c1f0 |
completed | May 17, 2026, 7:59 p.m. |
| NEDg | Description generation | batch_6a0a1f457fc48190a36c6cf8934fd5d3 |
completed | May 17, 2026, 8:04 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a1fc13900819098ee66684dfdff95 |
completed | May 17, 2026, 8:06 p.m. |
Created at: April 16, 2026, 6:45 p.m.