Triple
T4333308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2nd Commando Regiment |
E97403
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
2CDO
2CDO is the commonly used abbreviation for the Australian Army’s elite 2nd Commando Regiment, a special forces unit specializing in high-readiness, direct action, and counter-terrorism operations.
|
E431971
|
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: 2CDO | Statement: [2nd Commando Regiment, abbreviation, 2CDO]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 2CDO Context triple: [2nd Commando Regiment, abbreviation, 2CDO]
-
A.
C-2
C-2 is a commuter rail line within the Cercanías Madrid network that connects central Madrid with its surrounding metropolitan areas.
-
B.
c2c
c2c is a British train operating company providing commuter and regional rail services between London and parts of Essex along the Thames estuary.
-
C.
D-2
D-2 was a 1993 German-led Spacelab space shuttle mission focused on microgravity and life sciences research in low Earth orbit.
-
D.
CADA
CADA is a Colorado state civil rights law that prohibits discrimination in areas such as employment, housing, and public accommodations.
-
E.
Cif
Cif is a household cleaning product brand known for its creams and sprays used to remove tough dirt and stains from various surfaces.
- 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: 2CDO Triple: [2nd Commando Regiment, abbreviation, 2CDO]
Generated description
2CDO is the commonly used abbreviation for the Australian Army’s elite 2nd Commando Regiment, a special forces unit specializing in high-readiness, direct action, and counter-terrorism operations.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 2CDO Target entity description: 2CDO is the commonly used abbreviation for the Australian Army’s elite 2nd Commando Regiment, a special forces unit specializing in high-readiness, direct action, and counter-terrorism operations.
-
A.
C-2
C-2 is a commuter rail line within the Cercanías Madrid network that connects central Madrid with its surrounding metropolitan areas.
-
B.
c2c
c2c is a British train operating company providing commuter and regional rail services between London and parts of Essex along the Thames estuary.
-
C.
D-2
D-2 was a 1993 German-led Spacelab space shuttle mission focused on microgravity and life sciences research in low Earth orbit.
-
D.
CADA
CADA is a Colorado state civil rights law that prohibits discrimination in areas such as employment, housing, and public accommodations.
-
E.
Cif
Cif is a household cleaning product brand known for its creams and sprays used to remove tough dirt and stains from various surfaces.
- 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_69b3454662a481908fbcd0bbfaa3a0a4 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3514faaac819081475681fd10da24 |
completed | March 12, 2026, 11:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5d0a634308190ba4d8c8dc07814ae |
completed | March 14, 2026, 9:18 p.m. |
| NEDg | Description generation | batch_69b5d47416fc8190b8a177cbdcc23399 |
completed | March 14, 2026, 9:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5d4e5e24c8190980bc545ca0d339d |
completed | March 14, 2026, 9:36 p.m. |
Created at: March 12, 2026, 11:13 p.m.