Triple
T4403428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Holden LX Torana |
E93668
|
entity |
| Predicate | performanceVariant |
P4680
|
FINISHED |
| Object |
SL/R 5000
The SL/R 5000 is a high-performance V8 sports sedan version of the Holden LX Torana, renowned in Australia for its motorsport heritage and muscle car status.
|
E438232
|
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: SL/R 5000 | Statement: [Holden LX Torana, performanceVariant, SL/R 5000]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SL/R 5000 Context triple: [Holden LX Torana, performanceVariant, SL/R 5000]
-
A.
SL1
SL1 is a Boston bus rapid transit route on the MBTA Silver Line that connects downtown with Logan International Airport.
-
B.
SLV
SLV is the three-letter ISO 3166-1 alpha-3 country code assigned to El Salvador.
-
C.
SL3
SL3 is a branch of Boston’s MBTA Silver Line bus rapid transit system that connects South Station with Chelsea via the Seaport and East Boston tunnels.
-
D.
SL4
SL4 is a branch of Boston’s MBTA Silver Line bus rapid transit service that runs between downtown and the Seaport/South Station area.
-
E.
SL2
SL2 is a branch of Boston’s MBTA Silver Line bus rapid transit service that connects South Station with the Seaport and Design Center area.
- 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: SL/R 5000 Triple: [Holden LX Torana, performanceVariant, SL/R 5000]
Generated description
The SL/R 5000 is a high-performance V8 sports sedan version of the Holden LX Torana, renowned in Australia for its motorsport heritage and muscle car status.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SL/R 5000 Target entity description: The SL/R 5000 is a high-performance V8 sports sedan version of the Holden LX Torana, renowned in Australia for its motorsport heritage and muscle car status.
-
A.
SL1
SL1 is a Boston bus rapid transit route on the MBTA Silver Line that connects downtown with Logan International Airport.
-
B.
SLV
SLV is the three-letter ISO 3166-1 alpha-3 country code assigned to El Salvador.
-
C.
SL3
SL3 is a branch of Boston’s MBTA Silver Line bus rapid transit system that connects South Station with Chelsea via the Seaport and East Boston tunnels.
-
D.
SL4
SL4 is a branch of Boston’s MBTA Silver Line bus rapid transit service that runs between downtown and the Seaport/South Station area.
-
E.
SL2
SL2 is a branch of Boston’s MBTA Silver Line bus rapid transit service that connects South Station with the Seaport and Design Center area.
- 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_69b345158c748190a2c040fce2da9980 |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b352d1af608190ac06d50433cf24bb |
completed | March 12, 2026, 11:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5f5fc9f508190a31adb0758555dfa |
completed | March 14, 2026, 11:57 p.m. |
| NEDg | Description generation | batch_69b5f9ccfb708190be00532e7f512a0c |
completed | March 15, 2026, 12:14 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5fa9d7fec81908b53c2e45d0c7fe6 |
completed | March 15, 2026, 12:17 a.m. |
Created at: March 12, 2026, 11:28 p.m.