Triple
T3601820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chief of Army Reserve |
E76272
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object |
CAR
CAR is the commonly used abbreviation for the Chief of Army Reserve, the senior leader responsible for commanding and overseeing the United States Army Reserve.
|
E371329
|
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: CAR | Statement: [Chief of Army Reserve, hasAbbreviation, CAR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CAR Context triple: [Chief of Army Reserve, hasAbbreviation, CAR]
-
A.
CAR
CAR is a research center dedicated to advancing the understanding, diagnosis, and treatment of autism spectrum disorders through scientific study and clinical collaboration.
-
B.
CAR
CAR is the standard NHL abbreviation for the Carolina Hurricanes professional ice hockey team.
-
C.
CAR
CAR is the standard three-letter abbreviation used for the NFL team Carolina Panthers.
-
D.
Cars
Cars is a 2006 Pixar animated film that follows a hotshot race car who discovers friendship and humility in a forgotten desert town.
-
E.
AUTO
AUTO is the autopilot robot aboard the starliner Axiom in Pixar's film "WALL-E," serving as the primary antagonist enforcing the ship's directive to never return to Earth.
- 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: CAR Triple: [Chief of Army Reserve, hasAbbreviation, CAR]
Generated description
CAR is the commonly used abbreviation for the Chief of Army Reserve, the senior leader responsible for commanding and overseeing the United States Army Reserve.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: CAR Target entity description: CAR is the commonly used abbreviation for the Chief of Army Reserve, the senior leader responsible for commanding and overseeing the United States Army Reserve.
-
A.
CAR
CAR is a research center dedicated to advancing the understanding, diagnosis, and treatment of autism spectrum disorders through scientific study and clinical collaboration.
-
B.
CAR
CAR is the standard NHL abbreviation for the Carolina Hurricanes professional ice hockey team.
-
C.
CAR
CAR is the standard three-letter abbreviation used for the NFL team Carolina Panthers.
-
D.
Cars
Cars is a 2006 Pixar animated film that follows a hotshot race car who discovers friendship and humility in a forgotten desert town.
-
E.
AUTO
AUTO is the autopilot robot aboard the starliner Axiom in Pixar's film "WALL-E," serving as the primary antagonist enforcing the ship's directive to never return to Earth.
- 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_69ad85d93dcc819094fba90cf70f4996 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc1dd264c819098796f5f50f251be |
completed | March 8, 2026, 6:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4031dce448190b112ba4d5fa16ee0 |
completed | March 13, 2026, 12:29 p.m. |
| NEDg | Description generation | batch_69b4039ebeb88190b3e2e87621939391 |
completed | March 13, 2026, 12:31 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b408778220819086935bfa9c0dd4fd |
completed | March 13, 2026, 12:52 p.m. |
Created at: March 8, 2026, 3:22 p.m.