Triple
T16794998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2nd Battalion, Royal Australian Regiment |
E408208
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | 2 RAR |
E406829
|
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: 2 RAR | Statement: [2nd Battalion, Royal Australian Regiment, nickname, 2 RAR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 2 RAR Context triple: [2nd Battalion, Royal Australian Regiment, nickname, 2 RAR]
-
A.
RAR
chosen
RAR is the Royal Australian Regiment, the principal regular infantry regiment of the Australian Army known for its service in major conflicts since World War II.
-
B.
RAR
RAR is the IATA airport code for Rarotonga International Airport, the main air gateway to the Cook Islands in the South Pacific.
-
C.
TAR
TAR is the commonly used abbreviation for the Intergovernmental Panel on Climate Change’s Third Assessment Report on climate change.
-
D.
TAR
TAR is a Mexican regional airline operating domestic passenger flights to various destinations across the country.
-
E.
TAR
TAR is the standard abbreviation for the Tampa Tarpons, a Minor League Baseball team based in Tampa, Florida.
- 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_69d88393905081908d00a86b99996ac8 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b2a96d888190a9876c3784bb7f95 |
completed | April 18, 2026, 4:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00ab109694819094c696904faf0418 |
completed | May 10, 2026, 3:58 p.m. |
Created at: April 10, 2026, 5:22 a.m.