Triple
T3512723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Recruit Training Regiment |
E74232
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object |
RTR
RTR is the commonly used nickname for the Recruit Training Regiment, a military unit responsible for initial training of new recruits.
|
E366335
|
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: RTR | Statement: [Recruit Training Regiment, nickname, RTR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: RTR Context triple: [Recruit Training Regiment, nickname, RTR]
-
A.
TRR
TRR is the IATA airport code for Trincomalee Airport in Sri Lanka.
-
B.
RTA
RTA is the common abbreviation for the Regional Transportation Authority of Northeastern Illinois, the agency that oversees public transit services in the Chicago metropolitan area.
-
C.
TRV
TRV is the stock ticker symbol for The Travelers Companies, a major U.S.-based insurance provider known for its property and casualty insurance products.
-
D.
RTG
RTG (Radioisotope Thermoelectric Generator) is a long-lived power system that converts heat from the natural decay of radioactive material into electricity, commonly used on deep-space missions like Voyager 2.
-
E.
RTM
RTM is the commonly used abbreviation for Rosetta Terminology Mapping, a system for standardizing and aligning terminology across different datasets or domains.
- 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: RTR Triple: [Recruit Training Regiment, nickname, RTR]
Generated description
RTR is the commonly used nickname for the Recruit Training Regiment, a military unit responsible for initial training of new recruits.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: RTR Target entity description: RTR is the commonly used nickname for the Recruit Training Regiment, a military unit responsible for initial training of new recruits.
-
A.
TRR
TRR is the IATA airport code for Trincomalee Airport in Sri Lanka.
-
B.
RTA
RTA is the common abbreviation for the Regional Transportation Authority of Northeastern Illinois, the agency that oversees public transit services in the Chicago metropolitan area.
-
C.
TRV
TRV is the stock ticker symbol for The Travelers Companies, a major U.S.-based insurance provider known for its property and casualty insurance products.
-
D.
RTG
RTG (Radioisotope Thermoelectric Generator) is a long-lived power system that converts heat from the natural decay of radioactive material into electricity, commonly used on deep-space missions like Voyager 2.
-
E.
TRB
TRB was the former stock ticker symbol for Tribune Company, a major American media conglomerate known for owning newspapers and television stations.
- 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_69ad85cfb5c881909c9a2edd9d6043cc |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc10b6b48190bedfed6d34afc425 |
completed | March 8, 2026, 6:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b37e76c3a08190831402ff0c680196 |
completed | March 13, 2026, 3:03 a.m. |
| NEDg | Description generation | batch_69b38232467c81909eb831bb0747cb77 |
completed | March 13, 2026, 3:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b385f078d48190a72e61c59aa27e43 |
completed | March 13, 2026, 3:35 a.m. |
Created at: March 8, 2026, 3:19 p.m.