Triple
T12341768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queensland Department of Transport and Main Roads |
E294242
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
TMR
TMR is the Queensland Government agency responsible for planning, managing, and regulating the state’s transport systems and major road infrastructure.
|
E978850
|
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: TMR | Statement: [Queensland Department of Transport and Main Roads, abbreviation, TMR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TMR Context triple: [Queensland Department of Transport and Main Roads, abbreviation, TMR]
-
A.
TMO
TMO is the stock ticker symbol for Thermo Fisher Scientific, a leading global provider of scientific instruments, reagents, and laboratory services.
-
B.
TM
TM is the New York Stock Exchange ticker symbol for Toyota Motor Corporation, the Japanese multinational automotive manufacturer.
-
C.
TMB
TMB is the commonly used abbreviation for the Technical Management Board, a governing body that oversees and coordinates technical and standardization activities within its organization.
-
D.
TMB
TMB is the main public transportation operator in the Barcelona metropolitan area, managing the city’s metro and bus networks.
-
E.
TRR
TRR is the IATA airport code for Trincomalee Airport in Sri Lanka.
- 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: TMR Triple: [Queensland Department of Transport and Main Roads, abbreviation, TMR]
Generated description
TMR is the Queensland Government agency responsible for planning, managing, and regulating the state’s transport systems and major road infrastructure.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: TMR Target entity description: TMR is the Queensland Government agency responsible for planning, managing, and regulating the state’s transport systems and major road infrastructure.
-
A.
TMO
TMO is the stock ticker symbol for Thermo Fisher Scientific, a leading global provider of scientific instruments, reagents, and laboratory services.
-
B.
TM
TM is the New York Stock Exchange ticker symbol for Toyota Motor Corporation, the Japanese multinational automotive manufacturer.
-
C.
TMB
TMB is the commonly used abbreviation for the Technical Management Board, a governing body that oversees and coordinates technical and standardization activities within its organization.
-
D.
TMB
TMB is the main public transportation operator in the Barcelona metropolitan area, managing the city’s metro and bus networks.
-
E.
TRR
TRR is the IATA airport code for Trincomalee Airport in Sri Lanka.
- 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_69d6ab6ccbec8190b09e2d357aa80064 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f7758dc8190bbc6a9ad00b01dce |
completed | April 10, 2026, 6:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f62aaa1d548190be065412aab70385 |
completed | May 2, 2026, 4:47 p.m. |
| NEDg | Description generation | batch_69f62c55aacc8190a0544306825bdfab |
completed | May 2, 2026, 4:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f62d51ab8081909c6f534051019dca |
completed | May 2, 2026, 4:58 p.m. |
Created at: April 8, 2026, 9:53 p.m.