Triple
T15322845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Recruit Training Regiment |
E366335
|
entity |
| Predicate | hasNickname |
P39
|
FINISHED |
| Object | RTR |
E366335
|
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: RTR | Statement: [Recruit Training Regiment, hasNickname, RTR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: RTR Context triple: [Recruit Training Regiment, hasNickname, RTR]
-
A.
RTR
RTR is a Swiss public broadcasting division that produces and distributes radio, television, and online content in the Romansh language.
-
B.
RTR
chosen
RTR is the commonly used nickname for the Recruit Training Regiment, a military unit responsible for initial training of new recruits.
-
C.
TRR
TRR is the IATA airport code for Trincomalee Airport in Sri Lanka.
-
D.
RTRA
RTRA is the abbreviation for the Royal Tank Regiment Association, an organization that supports and connects current and former members of the Royal Tank Regiment.
-
E.
TRTS
TRTS is the commonly used abbreviation for the Taipei Metro rapid transit system serving the Taipei metropolitan area in Taiwan.
- 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_69d85a121520819093dcce999fdefe1a |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03dd5ce0c819093c9a14de549dff6 |
completed | April 16, 2026, 1:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fef8aaef608190bd3ec9fdd215afbb |
completed | May 9, 2026, 9:04 a.m. |
Created at: April 10, 2026, 3:16 a.m.