Triple
T7203176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tarasov Division |
E148598
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
TAR Division
TAR Division is the abbreviated name for the Tarasov Division, likely denoting a specific organizational or military unit associated with the Tarasov designation.
|
E649082
|
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: TAR Division | Statement: [Tarasov Division, abbreviation, TAR Division]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TAR Division Context triple: [Tarasov Division, abbreviation, TAR Division]
-
A.
IRT Division
The IRT Division is one of the original operating divisions of the New York City Subway, historically derived from the Interborough Rapid Transit Company and encompassing the system’s numbered subway lines.
-
B.
TAR
TAR is a Mexican regional airline operating domestic passenger flights to various destinations across the country.
-
C.
TAR
TAR is the ICAO airline designator assigned to Tunisair, the national flag carrier of Tunisia.
-
D.
TAR
TAR is the commonly used abbreviation for the Intergovernmental Panel on Climate Change’s Third Assessment Report on climate change.
-
E.
TAR
TAR is the standard abbreviation for the Tampa Tarpons, a Minor League Baseball team based in Tampa, Florida.
- 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: TAR Division Triple: [Tarasov Division, abbreviation, TAR Division]
Generated description
TAR Division is the abbreviated name for the Tarasov Division, likely denoting a specific organizational or military unit associated with the Tarasov designation.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: TAR Division Target entity description: TAR Division is the abbreviated name for the Tarasov Division, likely denoting a specific organizational or military unit associated with the Tarasov designation.
-
A.
IRT Division
The IRT Division is one of the original operating divisions of the New York City Subway, historically derived from the Interborough Rapid Transit Company and encompassing the system’s numbered subway lines.
-
B.
TAR
TAR is a Mexican regional airline operating domestic passenger flights to various destinations across the country.
-
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 the ICAO airline designator assigned to Tunisair, the national flag carrier of Tunisia.
-
E.
TAR
TAR is the standard abbreviation for the Tampa Tarpons, a Minor League Baseball team based in Tampa, Florida.
- 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_69c687e8cf188190b5f3ecffd681f04e |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6e94a9ee4819086de79fcdfa1836a |
completed | March 27, 2026, 8:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7bfb5e27c8190867fb4968dea2e4e |
completed | March 28, 2026, 11:47 a.m. |
| NEDg | Description generation | batch_69c7c0e45cc48190bea1daf65e5650b3 |
completed | March 28, 2026, 11:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7c13e64208190ba76f5c6a0df40db |
completed | March 28, 2026, 11:53 a.m. |
Created at: March 27, 2026, 2:52 p.m.